Linear Regression Explained | Papers With Code

Linear Regression

Linear Regression is a method for modelling a relationship between a dependent variable and independent variables. These models can be fit with numerous approaches. The most common is least squares, where we minimize the mean square error between the predicted values $\hat{y} = \textbf{X}\hat{\beta}$ and actual values $y$: $\left(y-\textbf{X}\beta\right)^{2}$.

We can also define the problem in probabilistic terms as a generalized linear model (GLM) where the pdf is a Gaussian distribution, and then perform maximum likelihood estimation to estimate $\hat{\beta}$.

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Latest Papers

PAPER	DATE
Quantum differentially private sparse regression learning Yuxuan Du • Min-Hsiu Hsieh • Tongliang Liu • Shan You • Dacheng Tao	2020-07-23
Using local dynamics to explain analog forecasting of chaotic systems P Platzer • P. Yiou • P. Naveau • P Tandeo • Y Zhen • P Ailliot • J-F Filipot	2020-07-22
Learning from Data to Speed-up Sorted Table Search Procedures: Methodology and Practical Guidelines Domenico Amato • Giosué Lo Bosco • Raffaele Giancarlo	2020-07-20
Optimal Robust Linear Regression in Nearly Linear Time Yeshwanth Cherapanamjeri • Efe Aras • Nilesh Tripuraneni • Michael I. Jordan • Nicolas Flammarion • Peter L. Bartlett	2020-07-16
Forecasting Hyponatremia in hospitalized patients Using Multilayer Perceptron and Multivariate Linear Regression Techniques Prasannavenkatesan Theerthagiri	2020-07-15
An Uncertainty-based Human-in-the-loop System for Industrial Tool Wear Analysis Alexander Treiss • Jannis Walk • Niklas Kühl	2020-07-14
A spectral algorithm for robust regression with subgaussian rates Jules Depersin	2020-07-12
Federated Learning's Blessing: FedAvg has Linear Speedup Zhaonan Qu • Kaixiang Lin • Jayant Kalagnanam • Zhaojian Li • Jiayu Zhou • Zhengyuan Zhou	2020-07-11
Differentially Private Simple Linear Regression Daniel Alabi • Audra McMillan • Jayshree Sarathy • Adam Smith • Salil Vadhan	2020-07-10
Robust Geodesic Regression \| Ha-Young Shin • Hee-Seok Oh	2020-07-09
Coded Computing for Federated Learning at the Edge Saurav Prakash • Sagar Dhakal • Mustafa Akdeniz • A. Salman Avestimehr • Nageen Himayat	2020-07-07
Piecewise Linear Regression via a Difference of Convex Functions \| Ali Siahkamari • Aditya Gangrade • Brian Kulis • Venkatesh Saligrama	2020-07-05
Coded Distributed Computing with Partial Recovery Emre Ozfatura • Sennur Ulukus • Deniz Gunduz	2020-07-04
Partial Trace Regression and Low-Rank Kraus Decomposition Hachem Kadri • Stéphane Ayache • Riikka Huusari • Alain Rakotomamonjy • Liva Ralaivola	2020-07-02
Efficient computation and analysis of distributional Shapley values Yongchan Kwon • Manuel A. Rivas • James Zou	2020-07-02
Decentralized Stochastic Gradient Langevin Dynamics and Hamiltonian Monte Carlo Mert Gürbüzbalaban • Xuefeng Gao • Yuanhan Hu • Lingjiong Zhu	2020-07-01
Online Robust Regression via SGD on the l1 loss Scott Pesme • Nicolas Flammarion	2020-07-01
Robust Linear Regression: Optimal Rates in Polynomial Time Ainesh Bakshi • Adarsh Prasad	2020-06-29
STORM: Foundations of End-to-End Empirical Risk Minimization on the Edge Benjamin Coleman • Gaurav Gupta • John Chen • Anshumali Shrivastava	2020-06-25
Active Online Domain Adaptation Yining Chen • Haipeng Luo • Tengyu Ma • Chicheng Zhang	2020-06-25
Distributionally-Robust Machine Learning Using Locally Differentially-Private Data Farhad Farokhi	2020-06-24
The Macroeconomy as a Random Forest Philippe Goulet Coulombe	2020-06-23
Statistical Mechanics of Generalization in Kernel Regression \| Abdulkadir Canatar • Blake Bordelon • Cengiz Pehlevan	2020-06-23
Exact Support Recovery in Federated Regression with One-shot Communication Adarsh Barik • Jean Honorio	2020-06-22
Learned Uncertainty-Aware (LUNA) Bases for Bayesian Regression using Multi-Headed Auxiliary Networks Sujay Thakur • Cooper Lorsung • Yaniv Yacoby • Finale Doshi-Velez • Weiwei Pan	2020-06-21
Transfer Learning for High-dimensional Linear Regression: Prediction, Estimation, and Minimax Optimality Sai Li • T. Tony Cai • Hongzhe Li	2020-06-18
Least Squares Regression with Markovian Data: Fundamental Limits and Algorithms Guy Bresler • Prateek Jain • Dheeraj Nagaraj • Praneeth Netrapalli • Xian Wu	2020-06-16
The Reflectron: Exploiting geometry for learning generalized linear models Nicholas M. Boffi • Jean-Jacques E. Slotine	2020-06-15
The Statistical Cost of Robust Kernel Hyperparameter Tuning Raphael A. Meyer • Christopher Musco	2020-06-14
Sub-Seasonal Climate Forecasting via Machine Learning: Challenges, Analysis, and Advances Sijie He • Xinyan Li • Timothy DelSole • Pradeep Ravikumar • Arindam Banerjee	2020-06-14
PAC-Bayes unleashed: generalisation bounds with unbounded losses Maxime Haddouche • Benjamin Guedj • Omar Rivasplata • John Shawe-Taylor	2020-06-12
Double Double Descent: On Generalization Errors in Transfer Learning between Linear Regression Tasks Yehuda Dar • Richard G. Baraniuk	2020-06-12
Sparse recovery by reduced variance stochastic approximation Anatoli Juditsky • Andrei Kulunchakov • Hlib Tsyntseus	2020-06-11
Multiplicative noise and heavy tails in stochastic optimization Liam Hodgkinson • Michael W. Mahoney	2020-06-11
On Uniform Convergence and Low-Norm Interpolation Learning Lijia Zhou • D. J. Sutherland • Nathan Srebro	2020-06-10
Distribution Regression for Continuous-Time Processes via the Expected Signature Maud Lemercier • Cristopher Salvi • Theodoros Damoulas • Edwin V. Bonilla • Terry Lyons	2020-06-10
Robust Grouped Variable Selection Using Distributionally Robust Optimization Ruidi Chen • Ioannis Ch. Paschalidis	2020-06-10
Robustified Multivariate Regression and Classification Using Distributionally Robust Optimization under the Wasserstein Metric Ruidi Chen • Ioannis Ch. Paschalidis	2020-06-10
Homomorphic Sensing of Subspace Arrangements Liangzu Peng • Boshi Wang • Manolis C. Tsakiris	2020-06-09
On the Minimax Optimality of the EM Algorithm for Learning Two-Component Mixed Linear Regression Jeongyeol Kwon • Nhat Ho • Constantine Caramanis	2020-06-04
Inject Machine Learning into Significance Test for Misspecified Linear Models Jiaye Teng • Yang Yuan	2020-06-04
On lower bounds for the bias-variance trade-off Alexis Derumigny • Johannes Schmidt-Hieber	2020-05-30
Robust estimation via generalized quasi-gradients Banghua Zhu • Jiantao Jiao • Jacob Steinhardt	2020-05-28
Learning How To Learn Within An LSM-based Key-Value Store Yifan Dai • Yien Xu • Aishwarya Ganesan • Ramnatthan Alagappan • Brian Kroth • Andrea C. Arpaci-Dusseau • Remzi H. Arpaci-Dusseau	2020-05-28
Review of Mathematical frameworks for Fairness in Machine Learning Eustasio del Barrio • Paula Gordaliza • Jean-Michel Loubes	2020-05-26
Scalable penalized spatiotemporal land-use regression for ground-level nitrogen dioxide Kyle P Messier • Matthias Katzfuss	2020-05-19
BLAZE: Blazing Fast Privacy-Preserving Machine Learning Arpita Patra • Ajith Suresh	2020-05-18
Nested Model Averaging on Solution Path for High-dimensional Linear Regression Yang Feng • Qingfeng Liu	2020-05-16
Learning Rate Annealing Can Provably Help Generalization, Even for Convex Problems Preetum Nakkiran	2020-05-15
A Multi-Variate Triple-Regression Forecasting Algorithm for Long-Term Customized Allergy Season Prediction Xiaoyu Wu • David Borrelli • Zeyu Bai • Youzhi Liang	2020-05-10
Automatic Cross-Domain Transfer Learning for Linear Regression Liu Xinshun • He Xin • Mao Hui • Liu Jing • Lai Weizhong • Ye Qingwen	2020-05-08
A Locally Adaptive Interpretable Regression \| Lkhagvadorj Munkhdalai • Tsendsuren Munkhdalai • Keun Ho Ryu	2020-05-07
Prediction of Human Empathy based on EEG Cortical Asymmetry Andrea Kuijt • Maryam Alimardani	2020-05-06
Outlier-Robust Clustering of Non-Spherical Mixtures Ainesh Bakshi • Pravesh Kothari	2020-05-06
One-step regression and classification with crosspoint resistive memory arrays Zhong Sun • Giacomo Pedretti • Alessandro Bricalli • Daniele Ielmini	2020-05-05
On the Generalization Effects of Linear Transformations in Data Augmentation \| Sen Wu • Hongyang R. Zhang • Gregory Valiant • Christopher Ré	2020-05-02
Generalization Error of Generalized Linear Models in High Dimensions \| Melikasadat Emami • Mojtaba Sahraee-Ardakan • Parthe Pandit • Sundeep Rangan • Alyson K. Fletcher	2020-05-01
Generalization Error for Linear Regression under Distributed Learning Martin Hellkvist • Ayça Özçelikkale • Anders Ahlén	2020-04-30
The Impact of the Mini-batch Size on the Variance of Gradients in Stochastic Gradient Descent Xin Qian • Diego Klabjan	2020-04-27
ExpDNN: Explainable Deep Neural Network Chi-Hua Chen	2020-04-26
Active Learning for Gaussian Process Considering Uncertainties with Application to Shape Control of Composite Fuselage Xiaowei Yue • Yuchen Wen • Jeffrey H. Hunt • Jianjun Shi	2020-04-23
Normalizing Flow Regression Yonatan Woodbridge • Gal Elidan • Ami Wiesel	2020-04-21
Utilizing Mask R-CNN for Waterline Detection in Canoe Sprint Video Analysis Marie-Sophie von Braun • Patrick Frenzel • Christian Käding • Mirco Fuchs	2020-04-20
Learning Entangled Single-Sample Distributions via Iterative Trimming Hui Yuan • Yingyu Liang	2020-04-20
Differentially Private Linear Regression over Fully Decentralized Datasets Yang Liu • Xiong Zhang • Shuqi Qin • Xiaoping Lei	2020-04-16
Secret Sharing based Secure Regressions with Applications Chaochao Chen • Liang Li • Wenjing Fang • Jun Zhou • Li Wang • Lei Wang • Shuang Yang • Alex Liu • Hao Wang	2020-04-10
Large-scale spatiotemporal photonic reservoir computer for image classification Piotr Antonik • Nicolas Marsal • Damien Rontani	2020-04-06
Exploiting context dependence for image compression with upsampling Jarek Duda	2020-04-06
Using Machine Learning Approach for Computational Substructure in Real-Time Hybrid Simulation Elif Ecem Bas • Mohamed A. Moustafa • David Feil-Seifer • Janelle Blankenburg	2020-04-04
Variable fusion for Bayesian linear regression via spike-and-slab priors Shengyi Wu • Kaito Shimamura • Kohei Yoshikawa • Kazuaki Murayama • Shuichi Kawano	2020-03-30
Obliviousness Makes Poisoning Adversaries Weaker Sanjam Garg • Somesh Jha • Saeed Mahloujifar • Mohammad Mahmoody • Abhradeep Thakurta	2020-03-26
Instance Credibility Inference for Few-Shot Learning \| Yikai Wang • Chengming Xu • Chen Liu • Li Zhang • Yanwei Fu	2020-03-26
Dimension Independent Generalization Error with Regularized Online Optimization Xi Chen • Qiang Liu • Xin T. Tong	2020-03-25
Logarithmic Regret Bound in Partially Observable Linear Dynamical Systems Sahin Lale • Kamyar Azizzadenesheli • Babak Hassibi • Anima Anandkumar	2020-03-25
Analysis of Greenhouse Gases Shalin Shah	2020-03-21
Efficiently Calibrating Cable-Driven Surgical Robots with RGBD Fiducial Sensing and Recurrent Neural Networks Minho Hwang • Brijen Thananjeyan • Samuel Paradis • Daniel Seita • Jeffrey Ichnowski • Danyal Fer • Thomas Low • Ken Goldberg	2020-03-19
Linear Regression without Correspondences via Concave Minimization Liangzu Peng • Manolis C. Tsakiris	2020-03-17
Pool-Based Unsupervised Active Learning for Regression Using Iterative Representativeness-Diversity Maximization (iRDM) Ziang Liu • Xue Jiang • Hanbin Luo • Weili Fang • Jiajing Liu • Dongrui Wu	2020-03-17
Improving predictions by nonlinear regression models from outlying input data William W. Hsieh	2020-03-17
Exploring Gaussian mixture model framework for speaker adaptation of deep neural network acoustic models Natalia Tomashenko • Yuri Khokhlov • Yannick Esteve	2020-03-15
A Time Series Approach To Player Churn and Conversion in Videogames Ana Fernández del Río • Anna Guitart • África Periáñez	2020-03-13
Short-Term Forecasting of CO2 Emission Intensity in Power Grids by Machine Learning Kenneth Leerbeck • Peder Bacher • Rune Junker • Goran Goranović • Olivier Corradi • Razgar Ebrahimy • Anna Tveit • Henrik Madsen	2020-03-10
Optimal Regularization Can Mitigate Double Descent Preetum Nakkiran • Prayaag Venkat • Sham Kakade • Tengyu Ma	2020-03-04
Weighted Encoding Based Image Interpolation With Nonlocal Linear Regression Model Junchao Zhang	2020-03-04
An Information-Theoretic Approach to Personalized Explainable Machine Learning Alexander Jung • Pedro H. J. Nardelli	2020-03-01
Optimal Feature Manipulation Attacks Against Linear Regression Fuwei Li • Lifeng Lai • Shuguang Cui	2020-02-29
Provable Meta-Learning of Linear Representations Nilesh Tripuraneni • Chi Jin • Michael I. Jordan	2020-02-26
Understanding and Mitigating the Tradeoff Between Robustness and Accuracy Aditi Raghunathan • Sang Michael Xie • Fanny Yang • John Duchi • Percy Liang	2020-02-25
A Sample Complexity Separation between Non-Convex and Convex Meta-Learning Nikunj Saunshi • Yi Zhang • Mikhail Khodak • Sanjeev Arora	2020-02-25
Learning From Strategic Agents: Accuracy, Improvement, and Causality Yonadav Shavit • Benjamin Edelman • Brian Axelrod	2020-02-24
Reparameterizing Mirror Descent as Gradient Descent Ehsan Amid • Manfred K. Warmuth	2020-02-24
Precise Tradeoffs in Adversarial Training for Linear Regression Adel Javanmard • Mahdi Soltanolkotabi • Hamed Hassani	2020-02-24
The Sample Complexity of Meta Sparse Regression Zhanyu Wang • Jean Honorio	2020-02-22
Few-Shot Learning via Learning the Representation, Provably Simon S. Du • Wei Hu • Sham M. Kakade • Jason D. Lee • Qi Lei	2020-02-21
Generalisation error in learning with random features and the hidden manifold model Federica Gerace • Bruno Loureiro • Florent Krzakala • Marc Mézard • Lenka Zdeborová	2020-02-21
Efficient Learning of Model Weights via Changing Features During Training Marcell Beregi-Kovács • Ágnes Baran • András Hajdu	2020-02-21
Multiscale Non-stationary Stochastic Bandits Qin Ding • Cho-Jui Hsieh • James Sharpnack	2020-02-13
Training Two-Layer ReLU Networks with Gradient Descent is Inconsistent \| David Holzmüller • Ingo Steinwart	2020-02-12
More Data Can Expand the Generalization Gap Between Adversarially Robust and Standard Models Lin Chen • Yifei Min • Mingrui Zhang • Amin Karbasi	2020-02-11
Vision based body gesture meta features for Affective Computing Indigo J. D. Orton	2020-02-10
Mitigating Query-Flooding Parameter Duplication Attack on Regression Models with High-Dimensional Gaussian Mechanism Xiaoguang Li • Hui Li • Haonan Yan • Zelei Cheng • Wenhai Sun • Hui Zhu	2020-02-06
A Regression Tsetlin Machine with Integer Weighted Clauses for Compact Pattern Representation \| K. Darshana Abeyrathna • Ole-Christoffer Granmo • Morten Goodwin	2020-02-04
WeatherBench: A benchmark dataset for data-driven weather forecasting \| Stephan Rasp • Peter D. Dueben • Sebastian Scher • Jonathan A. Weyn • Soukayna Mouatadid • Nils Thuerey	2020-02-02
Overfitting Can Be Harmless for Basis Pursuit: Only to a Degree Peizhong Ju • Xiaojun Lin • Jia Liu	2020-02-02
Kernel Selection for Modal Linear Regression: Optimal Kernel and IRLS Algorithm Ryoya Yamasaki • Toshiyuki Tanaka	2020-01-30
Statistical Tests and Confidential Intervals as Thresholds for Quantum Neural Networks Do Ngoc Diep	2020-01-30
Data-Driven Discovery of Coarse-Grained Equations Joseph Bakarji • Daniel M. Tartakovsky	2020-01-30
Imputation for High-Dimensional Linear Regression Kabir Aladin Chandrasekher • Ahmed El Alaoui • Andrea Montanari	2020-01-24
The Reciprocal Bayesian LASSO \| Himel Mallick • Rahim Alhamzawi • Vladimir Svetnik	2020-01-23
Data-Driven Permanent Magnet Temperature Estimation in Synchronous Motors with Supervised Machine Learning Wilhelm Kirchgässner • Oliver Wallscheid • Joachim Böcker	2020-01-17
Unsupervised Pool-Based Active Learning for Linear Regression Ziang Liu • Dongrui Wu	2020-01-14
Backward Feature Correction: How Deep Learning Performs Deep Learning Zeyuan Allen-Zhu • Yuanzhi Li	2020-01-13
Choosing the Sample with Lowest Loss makes SGD Robust Vatsal Shah • Xiaoxia Wu • Sujay Sanghavi	2020-01-10
Multi-layer Optimizations for End-to-End Data Analytics Amir Shaikhha • Maximilian Schleich • Alexandru Ghita • Dan Olteanu	2020-01-10
Review of Probability Distributions for Modeling Count Data F. William Townes	2020-01-10
Stellar Property Statistics of Massive Halos from Cosmological Hydrodynamics Simulations: Common Kernel Shapes Dhayaa Anbajagane • August E. Evrard • Arya Farahi • David J. Barnes • Klaus Dolag • Ian G. McCarthy • Dylan Nelson • Annalisa Pillepich	2020-01-07
The Secret Revealer: Generative Model Inversion Attacks Against Deep Neural Networks Anonymous	2020-01-01
Distributed Online Optimization with Long-Term Constraints Deming Yuan • Alexandre Proutiere • Guodong Shi	2019-12-20
Quantifying the effect of representations on task complexity Julian Zilly • Lorenz Hetzel • Andrea Censi • Emilio Frazzoli	2019-12-19
Bayesian high-dimensional linear regression with generic spike-and-slab priors Bai Jiang • Qiang Sun	2019-12-19
Benchmarking the Neural Linear Model for Regression Sebastian W. Ober • Carl Edward Rasmussen	2019-12-18
More Data Can Hurt for Linear Regression: Sample-wise Double Descent Preetum Nakkiran	2019-12-16
Bayesian Linear Regression on Deep Representations John Moberg • Lennart Svensson • Juliano Pinto • Henk Wymeersch	2019-12-14
Exact expressions for double descent and implicit regularization via surrogate random design Michał Dereziński • Feynman Liang • Michael W. Mahoney	2019-12-10
Improved PAC-Bayesian Bounds for Linear Regression Vera Shalaeva • Alireza Fakhrizadeh Esfahani • Pascal Germain • Mihaly Petreczky	2019-12-06
Analysis of effectiveness of thresholding in perfusion ROI detection on T2-weighted MR images with abnormal brain anatomy Svitlana Alkhimova • Svitlana Sliusar	2019-12-05
Trident: Efficient 4PC Framework for Privacy Preserving Machine Learning Rahul Rachuri • Ajith Suresh	2019-12-05
Fast Sparse Group Lasso Yasutoshi Ida • Yasuhiro Fujiwara • Hisashi Kashima	2019-12-01
Partitioning Structure Learning for Segmented Linear Regression Trees \| Xiangyu Zheng • Song Xi Chen	2019-12-01
Efficient adjustment sets for population average treatment effect estimation in non-parametric causal graphical models Andrea Rotnitzky • Ezequiel Smucler	2019-12-01
Recursive Prediction of Graph Signals with Incoming Nodes Arun Venkitaraman • Saikat Chatterjee • Bo Wahlberg	2019-11-26
Joint Modeling of Local and Global Temporal Dynamics for Multivariate Time Series Forecasting with Missing Values Xianfeng Tang • Huaxiu Yao • Yiwei Sun • Charu Aggarwal • Prasenjit Mitra • Suhang Wang	2019-11-22
Bayesian Curiosity for Efficient Exploration in Reinforcement Learning Tom Blau • Lionel Ott • Fabio Ramos	2019-11-20
The Secret Revealer: Generative Model-Inversion Attacks Against Deep Neural Networks Yuheng Zhang • Ruoxi Jia • Hengzhi Pei • Wenxiao Wang • Bo Li • Dawn Song	2019-11-17
A Model of Double Descent for High-dimensional Binary Linear Classification Zeyu Deng • Abla Kammoun • Christos Thrampoulidis	2019-11-13
0-1 phase transitions in sparse spiked matrix estimation Jean Barbier • Nicolas Macris # 1 3D MULTI-PERSON POSE ESTIMATION (ABSOLUTE) ON MUPOTS-3D	2019-11-12
Sparse estimation via $\ell_q$ optimization method in high-dimensional linear regression Xin Li • Yaohua Hu • Chong Li • Xiaoqi Yang • Tianzi Jiang	2019-11-12
Tensor Regression Using Low-rank and Sparse Tucker Decompositions Talal Ahmed • Haroon Raja • Waheed U. Bajwa	2019-11-09
Missing Features Reconstruction and Its Impact on Classification Accuracy Magda Friedjungová • Daniel Vašata • Marcel Jiřina	2019-11-09
Explaining the Predictions of Any Image Classifier via Decision Trees Sheng Shi • Xinfeng Zhang • Wei Fan	2019-11-04
Modelling bid-ask spread conditional distributions using hierarchical correlation reconstruction Jarosław Duda • Robert Syrek • Henryk Gurgul	2019-11-04
Quantification of MagLIF morphology using the Mallat Scattering Transformation Michael E. Glinsky • Thomas W. Moore • William E. Lewis • Matthew R. Weis • Christopher A. Jennings • David A. Ampleford • Eric C. Harding • Patrick F. Knapp • Matthew. R. Gomez • Sophia E. Lussiez	2019-11-01
EnergyStar++: Towards more accurate and explanatory building energy benchmarking \| Pandarasamy Arjunan • Kameshwar Poolla • Clayton Miller	2019-10-30
Machine Learning-Based Analysis of Sperm Videos and Participant Data for Male Fertility Prediction Steven A. Hicks • Jorunn M. Andersen • Oliwia Witczak • Vajira Thambawita • Påll Halvorsen • Hugo L. Hammer • Trine B. Haugen • Michael A. Riegler	2019-10-29
Inference in High-Dimensional Linear Regression via Lattice Basis Reduction and Integer Relation Detection David Gamarnik • Eren C. Kızıldağ • Ilias Zadik	2019-10-24
Q-GADMM: Quantized Group ADMM for Communication Efficient Decentralized Machine Learning Anis Elgabli • Jihong Park • Amrit S. Bedi • Chaouki Ben Issaid • Mehdi Bennis • Vaneet Aggarwal	2019-10-23
Prediction of Reaction Time and Vigilance Variability from Spatiospectral Features of Resting-State EEG in a Long Sustained Attention Task Mastaneh Torkamani-Azar • Sumeyra Demir Kanik • Serap Aydin • Mujdat Cetin	2019-10-21
First order expansion of convex regularized estimators Pierre C Bellec • Arun K Kuchibhotla	2019-10-12
Efficient Symmetric Norm Regression via Linear Sketching Zhao Song • Ruosong Wang • Lin F. Yang • Hongyang Zhang • Peilin Zhong	2019-10-04
A Pseudo-Likelihood Approach to Linear Regression with Partially Shuffled Data Martin Slawski • Guoqing Diao • Emanuel Ben-David	2019-10-03
Expert2Coder: Capturing Divergent Brain Regions Using Mixture of Regression Experts Subba Reddy Oota • Naresh Manwani • Raju S. Bapi	2019-09-26
The column measure and Gradient-Free Gradient Boosting Tino Werner • Peter Ruckdeschel	2019-09-24
Tuning parameter calibration for prediction in personalized medicine \| Shih-Ting Huang • Yannick Düren • Kristoffer H. Hellton • Johannes Lederer	2019-09-23
A generalization of regularized dual averaging and its dynamics \| Shih-Kang Chao • Guang Cheng	2019-09-22
Does SLOPE outperform bridge regression? Shuaiwen Wang • Haolei Weng • Arian Maleki	2019-09-20
Weighted Linear Bandits for Non-Stationary Environments \| Yoan Russac • Claire Vernade • Olivier Cappé	2019-09-19
Exploring linearity of deep neural network trained QSM: QSMnet+ Woojin Jung • Jaeyeon Yoon • Joon Yul Choi • Jae Myung Kim • Yoonho Nam • Eung Yeop Kim • Jongho Lee	2019-09-17
Reproducibility of an airway tapering measurement in CT with application to bronchiectasis Kin Quan • Ryutaro Tanno • Rebecca J. Shipley • Jeremy S. Brown • Joseph Jacob • John R. Hurst • David J. Hawkes	2019-09-16
A Knowledge Transfer Framework for Differentially Private Sparse Learning Lingxiao Wang • Quanquan Gu	2019-09-13
Super learning for daily streamflow forecasting: Large-scale demonstration and comparison with multiple machine learning algorithms Hristos Tyralis • Georgia Papacharalampous • Andreas Langousis	2019-09-09
A scalable constructive algorithm for the optimization of neural network architectures Massimiliano Lupo Pasini • Junqi Yin • Ying Wai Li • Markus Eisenbach	2019-09-07
Regression-clustering for Improved Accuracy and Training Cost with Molecular-Orbital-Based Machine Learning Lixue Cheng • Nikola B. Kovachki • Matthew Welborn • Thomas F. Miller III	2019-09-04
Rewarding High-Quality Data via Influence Functions Adam Richardson • Aris Filos-Ratsikas • Boi Faltings	2019-08-30
A Concert-planning Tool for Independent Musicians by Machine Learning Models Xiaohan Yang • Qingyin Ge	2019-08-29
Generalizing Psychological Similarity Spaces to Unseen Stimuli Lucas Bechberger • Kai-Uwe Kühnberger	2019-08-25
A Three-Feature Model to Predict Colour Change Blindness Steven Le Moan • Marius Pedersen	2019-08-25
A deep learning model for segmentation of geographic atrophy to study its long-term natural history Bart Liefers • Johanna M. Colijn • Cristina González-Gonzalo • Timo Verzijden • Paul Mitchell • Carel B. Hoyng • Bram van Ginneken • Caroline C. W. Klaver • Clara I. Sánchez	2019-08-15
The generalization error of random features regression: Precise asymptotics and double descent curve Song Mei • Andrea Montanari	2019-08-14
Predicted disease compositions of human gliomas estimated from multiparametric MRI can predict endothelial proliferation, tumor grade, and overall survival Emily E Diller • Sha Cao • Beth Ey • Robert Lober • Jason G Parker	2019-08-06
Dueling Posterior Sampling for Preference-Based Reinforcement Learning \| Ellen R. Novoseller • Yibing Wei • Yanan Sui • Yisong Yue • Joel W. Burdick	2019-08-04
Method of Contraction-Expansion (MOCE) for Simultaneous Inference in Linear Models Fei Wang • Ling Zhou • Lu Tang • Peter X. -K. Song	2019-08-04
Risk Management via Anomaly Circumvent: Mnemonic Deep Learning for Midterm Stock Prediction Xinyi Li • Yinchuan Li • Xiao-Yang Liu • Christina Dan Wang	2019-08-03
Speech Recognition for Tigrinya language Using Deep Neural Network Approach Hafte Abera • Sebsibe H/mariam	2019-08-01
Airbnb Price Prediction Using Machine Learning and Sentiment Analysis \| Pouya Rezazadeh Kalehbasti • Liubov Nikolenko • Hoormazd Rezaei	2019-07-29
Effective and efficient ROI-wise visual encoding using an end-to-end CNN regression model and selective optimization \| Kai Qiao • Chi Zhang • Jian Chen • Linyuan Wang • Li Tong • Bin Yan	2019-07-27
Algorithmic Analysis and Statistical Estimation of SLOPE via Approximate Message Passing \| Zhiqi Bu • Jason Klusowski • Cynthia Rush • Weijie Su	2019-07-17
A Two-Stage Approach to Multivariate Linear Regression with Sparsely Mismatched Data Martin Slawski • Emanuel Ben-David • Ping Li	2019-07-16
Medical Concept Representation Learning from Claims Data and Application to Health Plan Payment Risk Adjustment Qiu-Yue Zhong • Andrew H. Fairless • Jasmine M. McCammon • Farbod Rahmanian	2019-07-15
Warfarin dose estimation on multiple datasets with automated hyperparameter optimisation and a novel software framework \| Gianluca Truda • Patrick Marais	2019-07-11
Unbiased estimators for random design regression Michał Dereziński • Manfred K. Warmuth • Daniel Hsu	2019-07-08
Copula Representations and Error Surface Projections for the Exclusive Or Problem Roy S. Freedman	2019-07-08
On a Randomized Multi-Block ADMM for Solving Selected Machine Learning Problems \| Mingxi Zhu • Kresimir Mihic • Yinyu Ye	2019-07-03
Protecting Privacy of Users in Brain-Computer Interface Applications Anisha Agarwal • Rafael Dowsley • Nicholas D. McKinney • Dongrui Wu • Chin-Teng Lin • Martine De Cock • Anderson C. A. Nascimento	2019-07-02
Benign Overfitting in Linear Regression Peter L. Bartlett • Philip M. Long • Gábor Lugosi • Alexander Tsigler	2019-06-26
Max-Affine Regression: Provable, Tractable, and Near-Optimal Statistical Estimation Avishek Ghosh • Ashwin Pananjady • Adityanand Guntuboyina • Kannan Ramchandran	2019-06-21
Active Linear Regression Xavier Fontaine • Pierre Perrault • Vianney Perchet	2019-06-20
Linear regression with stationary errors : the R package slm Emmanuel Caron • Jérôme Dedecker • Michel Bertrand	2019-06-15
Distributed High-dimensional Regression Under a Quantile Loss Function Xi Chen • Weidong Liu • Xiaojun Mao • Zhuoyi Yang	2019-06-13
Variance Estimation For Dynamic Regression via Spectrum Thresholding Mark Kozdoba • Edward Moroshko • Shie Mannor • Koby Crammer	2019-06-13
Bayesian experimental design using regularized determinantal point processes Michał Dereziński • Feynman Liang • Michael W. Mahoney	2019-06-10
Selection consistency of Lasso-based procedures for misspecified high-dimensional binary model and random regressors Mariusz Kubkowski • Jan Mielniczuk	2019-06-10
Complex Evolution Recurrent Neural Networks (ceRNNs) Izhak Shafran • Tom Bagby • R. J. Skerry-Ryan	2019-06-05
On the number of variables to use in principal component regression Ji Xu • Daniel Hsu	2019-06-04
JTML at SemEval-2019 Task 6: Offensive Tweets Identification using Convolutional Neural Networks Johnny Torres • Carmen Vaca	2019-06-01
Robust Nonparametric Difference-in-Differences Estimation Chen Lu • Xinkun Nie • Stefan Wager	2019-05-28
Parallel and Communication Avoiding Least Angle Regression K. Fountoulakis • S. Das • L. Grigori • M. W. Mahoney • J. Demmel	2019-05-27
What Can ResNet Learn Efficiently, Going Beyond Kernels? Zeyuan Allen-Zhu • Yuanzhi Li	2019-05-24
Deep-gKnock: nonlinear group-feature selection with deep neural network Guangyu Zhu • Tingting Zhao	2019-05-24
Exploring helical dynamos with machine learning \| Farrukh Nauman • Joonas Nättilä	2019-05-20
Merging versus Ensembling in Multi-Study Machine Learning: Theoretical Insight from Random Effects Zoe Guan • Giovanni Parmigiani • Prasad Patil	2019-05-17
A New Look at an Old Problem: A Universal Learning Approach to Linear Regression \| Koby Bibas • Yaniv Fogel • Meir Feder	2019-05-12
A Scalable Learned Index Scheme in Storage Systems Pengfei Li • Yu Hua • Pengfei Zuo • Jingnan Jia	2019-05-08
Characterizing the invariances of learning algorithms using category theory Kenneth D. Harris	2019-05-06
Learning Some Popular Gaussian Graphical Models without Condition Number Bounds Jonathan Kelner • Frederic Koehler • Raghu Meka • Ankur Moitra	2019-05-03
Meta-learners' learning dynamics are unlike learners' Neil C. Rabinowitz	2019-05-03
Rethinking learning rate schedules for stochastic optimization Rong Ge • Sham M. Kakade • Rahul Kidambi • Praneeth Netrapalli	2019-05-01
An Exhaustive Analysis of Lazy vs. Eager Learning Methods for Real-Estate Property Investment Setareh Rafatirad • Maryam Heidari	2019-05-01
Horseshoe Regularization for Machine Learning in Complex and Deep Models Anindya Bhadra • Jyotishka Datta • Yunfan Li • Nicholas G. Polson	2019-04-24
Objective Assessment of Social Skills Using Automated Language Analysis for Identification of Schizophrenia and Bipolar Disorder Rohit Voleti • Stephanie Woolridge • Julie M. Liss • Melissa Milanovic • Christopher R. Bowie • Visar Berisha	2019-04-24
Memory-Sample Tradeoffs for Linear Regression with Small Error Vatsal Sharan • Aaron Sidford • Gregory Valiant	2019-04-18
Constructing Parsimonious Analytic Models for Dynamic Systems via Symbolic Regression \| Erik Derner • Jiří Kubalík • Nicola Ancona • Robert Babuška	2019-03-27
Short-term Load Forecasting at Different Aggregation Levels with Predictability Analysis Yayu Peng • Yishen Wang • Xiao Lu • Haifeng Li • Di Shi • Zhiwei Wang • Jie Li	2019-03-26
Localized Linear Regression in Networked Data Alexander Jung • Nguyen Tran	2019-03-26
Implicit Regularization via Hadamard Product Over-Parametrization in High-Dimensional Linear Regression Peng Zhao • Yun Yang • Qiao-Chu He	2019-03-22
Convergence of Parameter Estimates for Regularized Mixed Linear Regression Models Taiyao Wang • Ioannis Ch. Paschalidis	2019-03-21
Byzantine Fault Tolerant Distributed Linear Regression Nirupam Gupta • Nitin H. Vaidya	2019-03-20
Adaptive Hard Thresholding for Near-optimal Consistent Robust Regression Arun Sai Suggala • Kush Bhatia • Pradeep Ravikumar • Prateek Jain	2019-03-19
Mutual Linear Regression-based Discrete Hashing Xingbo Liu • Xiushan Nie • Yilong Yin	2019-03-15
Personal Dynamic Cost-Aware Sensing for Latent Context Detection Saar Tal • Bracha Shapira • Lior Rokach	2019-03-13
Spike-and-Slab Group Lassos for Grouped Regression and Sparse Generalized Additive Models Ray Bai • Gemma E. Moran • Joseph Antonelli • Yong Chen • Mary R. Boland	2019-03-05
Multiple Learning for Regression in big data Xiang Liu • Ziyang Tang • Huyunting Huang • Tonglin Zhang • Baijian Yang	2019-03-03
On Robustness of Principal Component Regression Anish Agarwal • Devavrat Shah • Dennis Shen • Dogyoon Song	2019-02-28
Provable Approximations for Constrained $\ell_p$ Regression Ibrahim Jubran • David Cohn • Dan Feldman	2019-02-27
Cross validation in sparse linear regression with piecewise continuous nonconvex penalties and its acceleration Tomoyuki Obuchi • Ayaka Sakata	2019-02-27
Nonlinear generalization of the monotone single index model \| Zeljko Kereta • Timo Klock • Valeriya Naumova	2019-02-24
Prediction of Porosity and Permeability Alteration based on Machine Learning Algorithms Andrei Erofeev • Denis Orlov • Alexey Ryzhov • Dmitry Koroteev	2019-02-18
Exponentially-Modified Gaussian Mixture Model: Applications in Spectroscopy Sebastian Ament • John Gregoire • Carla Gomes	2019-02-14
Distributed Online Linear Regression Deming Yuan • Alexandre Proutiere • Guodong Shi	2019-02-13
Differential Description Length for Hyperparameter Selection in Machine Learning Mojtaba Abolfazli • Anders Host-Madsen • June Zhang	2019-02-13
The Cost of Privacy: Optimal Rates of Convergence for Parameter Estimation with Differential Privacy T. Tony Cai • Yichen Wang • Linjun Zhang	2019-02-12
Iterative Least Trimmed Squares for Mixed Linear Regression Yanyao Shen • Sujay Sanghavi	2019-02-10
Scalable Holistic Linear Regression Dimitris Bertsimas • Michael Lingzhi Li	2019-02-08
Secure multi-party linear regression at plaintext speed \| Jonathan M. Bloom	2019-01-28
The autofeat Python Library for Automated Feature Engineering and Selection \| Franziska Horn • Robert Pack • Michael Rieger	2019-01-22
Learning Direct and Inverse Transmission Matrices Daniele Ancora • Luca Leuzzi	2019-01-15
Spatial Filtering Pipeline Evaluation of Cortically Coupled Computer Vision System for Rapid Serial Visual Presentation Zhengwei Wang • Graham Healy • Alan F. Smeaton • Tomas E. Ward	2019-01-15
Predicting Individual Responses to Vasoactive Medications in Children with Septic Shock Nicole Fronda • Jessica Asencio • Cameron Carlin • David Ledbetter • Melissa Aczon • Randall Wetzel • Barry Markovitz	2019-01-15
Variational Bayesian Weighted Complex Network Reconstruction \| Shuang Xu • Chun-Xia Zhang • Pei Wang • Jiangshe Zhang	2018-12-11
Doubly Robust Bayesian Inference for Non-Stationary Streaming Data with \beta-Divergences Jeremias Knoblauch • Jack E. Jewson • Theodoros Damoulas	2018-12-01
\ell_1-regression with Heavy-tailed Distributions Lijun Zhang • Zhi-Hua Zhou	2018-12-01
Optimal Subsampling with Influence Functions Daniel Ting • Eric Brochu	2018-12-01
An Improved Analysis of Alternating Minimization for Structured Multi-Response Regression Sheng Chen • Arindam Banerjee	2018-12-01
Model-based targeted dimensionality reduction for neuronal population data Mikio Aoi • Jonathan W. Pillow	2018-12-01
Scalable Hyperparameter Transfer Learning Valerio Perrone • Rodolphe Jenatton • Matthias W. Seeger • Cedric Archambeau	2018-12-01
Sparse PCA from Sparse Linear Regression Guy Bresler • Sung Min Park • Madalina Persu	2018-11-25
Recovery guarantees for polynomial approximation from dependent data with outliers Lam Si Tung Ho • Hayden Schaeffer • Giang Tran • Rachel Ward	2018-11-25
Steerable Wavelet Scattering for 3D Atomic Systems with Application to Li-Si Energy Prediction Xavier Brumwell • Paul Sinz • Kwang Jin Kim • Yue Qi • Matthew Hirn	2018-11-21
Optical Flow Based Background Subtraction with a Moving Camera: Application to Autonomous Driving Sotirios Diamantas • Kostas Alexis	2018-11-16
Regularised Zero-Variance Control Variates Leah F. South • Antonietta Mira • Christopher Drovandi	2018-11-13
Scale calibration for high-dimensional robust regression Po-Ling Loh	2018-11-06
Prediction Error Meta Classification in Semantic Segmentation: Detection via Aggregated Dispersion Measures of Softmax Probabilities \| Matthias Rottmann • Pascal Colling • Thomas-Paul Hack • Robin Chan • Fabian Hüger • Peter Schlicht • Hanno Gottschalk	2018-11-01
From Gene Expression to Drug Response: A Collaborative Filtering Approach Cheng Qian • Nicholas D. Sidiropoulos • Magda Amiridi • Amin Emad	2018-10-29
Comparing Multilayer Perceptron and Multiple Regression Models for Predicting Energy Use in the Balkans Radmila Janković • Alessia Amelio	2018-10-26
Exploiting High-Level Semantics for No-Reference Image Quality Assessment of Realistic Blur Images \| Dingquan Li • Tingting Jiang • Ming Jiang	2018-10-18
Hunting for Discriminatory Proxies in Linear Regression Models Samuel Yeom • Anupam Datta • Matt Fredrikson	2018-10-16
An algebraic-geometric approach for linear regression without correspondences Manolis C. Tsakiris • Liangzu Peng • Aldo Conca • Laurent Kneip • Yuanming Shi • Hayoung Choi	2018-10-12
Global Convergence of EM Algorithm for Mixtures of Two Component Linear Regression Jeongyeol Kwon • Wei Qian • Constantine Caramanis • Yudong Chen • Damek Davis	2018-10-12
Which Has Better Visual Quality: The Clear Blue Sky or a Blurry Animal? \| Dingquan Li • Tingting Jiang • Weisi Lin • Ming Jiang	2018-10-11
A Unified Dynamic Approach to Sparse Model Selection Chendi Huang • Yuan Yao	2018-10-08
A Machine Learning-based Recommendation System for Swaptions Strategies Adriano Soares Koshiyama • Nick Firoozye • Philip Treleaven	2018-10-04
Correcting the bias in least squares regression with volume-rescaled sampling Michał Dereziński • Manfred K. Warmuth • Daniel Hsu	2018-10-04
Agnostic Sample Compression for Linear Regression Steve Hanneke • Aryeh Kontorovich • Menachem Sadigurschi	2018-10-03
Posterior Prototyping: Bridging the Gap between Bayesian Record Linkage and Regression Andee Kaplan • Brenda Betancourt • Rebecca C. Steorts	2018-10-02
plsRglm: Partial least squares linear and generalized linear regression for processing incomplete datasets by cross-validation and bootstrap techniques with R F. Bertrand • M. Maumy-Bertrand	2018-10-01
Distributed linear regression by averaging \| Edgar Dobriban • Yue Sheng	2018-09-30
Estimate the Warfarin Dose by Ensemble of Machine Learning Algorithms Zhiyuan Ma • Ping Wang • Zehui Gao • Ruobing Wang • Koroush Khalighi	2018-09-10
Characterizing the Influence of Features on Reading Difficulty Estimation for Non-native Readers Yi-Ting Huang • Meng Chang Chen • Yeali S. Sun	2018-08-29
The Mismatch Principle: The Generalized Lasso Under Large Model Uncertainties Martin Genzel • Gitta Kutyniok	2018-08-20
Optimal stopping via reinforced regression Denis Belomestny • John Schoenmakers • Vladimir Spokoiny • Bakhyt Zharkynbay	2018-08-07
Multi-Estimator Full Left Ventricle Quantification through Ensemble Learning Jiasha Liu • Xiang Li • Hui Ren • Quanzheng Li	2018-08-06
Relation Induction in Word Embeddings Revisited Zied Bouraoui • Shoaib Jameel • Steven Schockaert	2018-08-01
Local Linear Forests \| Rina Friedberg • Julie Tibshirani • Susan Athey • Stefan Wager	2018-07-30
Meta-Learning Priors for Efficient Online Bayesian Regression \| James Harrison • Apoorva Sharma • Marco Pavone	2018-07-24
Sign-Perturbed Sums: A New System Identification Approach for Constructing Exact Non-Asymptotic Confidence Regions in Linear Regression Models Balázs Cs. Csáji • Marco C. Campi • Erik Weyer	2018-07-22
The Incremental Proximal Method: A Probabilistic Perspective Ömer Deniz Akyildiz • Victor Elvira • Joaquin Miguez	2018-07-12
Proactive Intervention to Downtrend Employee Attrition using Artificial Intelligence Techniques Aasheesh Barvey • Jitin Kapila • Kumarjit Pathak	2018-07-11
Tournament Based Ranking CNN for the Cataract grading Dohyeun Kim • Tae Joon Jun • Daeyoung Kim • Youngsub Eom	2018-07-07
Robust Inference Under Heteroskedasticity via the Hadamard Estimator Edgar Dobriban • Weijie J. Su	2018-07-01
Conditional Sparse $\ell_p$-norm Regression With Optimal Probability John Hainline • Brendan Juba • Hai S. Le • David Woodruff	2018-06-26
Subspace Embedding and Linear Regression with Orlicz Norm Alexandr Andoni • Chengyu Lin • Ying Sheng • Peilin Zhong • Ruiqi Zhong	2018-06-17
Efficient sampling for Gaussian linear regression with arbitrary priors P. Richard Hahn • Jingyu He • Hedibert Lopes	2018-06-14
Direct Automated Quantitative Measurement of Spine via Cascade Amplifier Regression Network Shumao Pang • Stephanie Leung • Ilanit Ben Nachum • Qianjin Feng • Shuo Li	2018-06-14
Estimating Achilles tendon healing progress with convolutional neural networks Norbert Kapinski • Jakub Zielinski • Bartosz A. Borucki • Tomasz Trzcinski • Beata Ciszkowska-Lyson • Krzysztof S. Nowinski	2018-06-13
A semiparametric modeling approach using Bayesian Additive Regression Trees with an application to evaluate heterogeneous treatment effects Bret Zeldow • Vincent Lo Re III • Jason Roy	2018-06-11
Conditional Linear Regression \| Diego Calderon • Brendan Juba • Sirui Li • Zongyi Li • Lisa Ruan	2018-06-06
Doubly Robust Bayesian Inference for Non-Stationary Streaming Data with $β$-Divergences \| Jeremias Knoblauch • Jack Jewson • Theodoros Damoulas	2018-06-06
Adversarial Regression with Multiple Learners \| Liang Tong • Sixie Yu • Scott Alfeld • Yevgeniy Vorobeychik	2018-06-06
Reverse iterative volume sampling for linear regression Michał Dereziński • Manfred K. Warmuth	2018-06-06
Data-driven Localization and Estimation of Disturbance in the Interconnected Power System Hyang-Won Lee • Jianan Zhang • Eytan Modiano	2018-06-04
Signal and Noise Statistics Oblivious Orthogonal Matching Pursuit Sreejith Kallummil • Sheetal Kalyani	2018-06-02
Current and Future Psychological Health Prediction using Language and Socio-Demographics of Children for the CLPysch 2018 Shared Task Sharath Ch Guntuku • ra • Salvatore Giorgi • Lyle Ungar	2018-06-01
Can adult mental health be predicted by childhood future-self narratives? Insights from the CLPsych 2018 Shared Task Kylie Radford • Louise Lavrencic • Ruth Peters • Kim Kiely • Ben Hachey • Scott Nowson • Will Radford	2018-06-01
Efficient Algorithms and Lower Bounds for Robust Linear Regression Ilias Diakonikolas • Weihao Kong • Alistair Stewart	2018-05-31
Uniform regret bounds over $R^d$ for the sequential linear regression problem with the square loss Pierre Gaillard • Sébastien Gerchinovitz • Malo Huard • Gilles Stoltz	2018-05-29
Optimal ridge penalty for real-world high-dimensional data can be zero or negative due to the implicit ridge regularization \| Dmitry Kobak • Jonathan Lomond • Benoit Sanchez	2018-05-28
Sequential adaptive elastic net approach for single-snapshot source localization \| Muhammad Naveed Tabassum • Esa Ollila	2018-05-19
$\ell_1$-regression with Heavy-tailed Distributions Lijun Zhang • Zhi-Hua Zhou	2018-05-02
Novel Prediction Techniques Based on Clusterwise Linear Regression \| Igor Gitman • Jieshi Chen • Eric Lei • Artur Dubrawski	2018-04-28
Moving Beyond Sub-Gaussianity in High-Dimensional Statistics: Applications in Covariance Estimation and Linear Regression Arun Kumar Kuchibhotla • Abhishek Chakrabortty	2018-04-08
Stochastic EM for Shuffled Linear Regression Abubakar Abid • James Zou	2018-04-02
Improving the Flexibility and Robustness of Model-Based Derivative-Free Optimization Solvers Coralia Cartis • Jan Fiala • Benjamin Marteau • Lindon Roberts	2018-03-31
AI Blue Book: Vehicle Price Prediction using Visual Features \| Richard R. Yang • Steven Chen • Edward Chou	2018-03-29
Cross-validation in high-dimensional spaces: a lifeline for least-squares models and multi-class LDA \| Matthias S. Treder	2018-03-27
Determinantal Point Processes for Coresets Nicolas Tremblay • Simon Barthelmé • Pierre-Olivier Amblard	2018-03-23
A Comprehensive Analysis of Deep Regression \| Stéphane Lathuilière • Pablo Mesejo • Xavier Alameda-Pineda • Radu Horaud	2018-03-22
Opposite neighborhood: a new method to select reference points of minimal learning machines \| Madson Luiz Dantas Dias • Lucas Silva De Sousa • Ajalmar Rêgo da Rocha Neto • Amauri H. de Souza Júnior	2018-03-22
Graph-based regularization for regression problems with alignment and highly-correlated designs Yuan Li • Benjamin Mark • Garvesh Raskutti • Rebecca Willett • Hyebin Song • David Neiman	2018-03-20
High Dimensional Linear Regression using Lattice Basis Reduction David Gamarnik • Ilias Zadik	2018-03-18
Scalable Algorithms for Learning High-Dimensional Linear Mixed Models \| Zilong Tan • Kimberly Roche • Xiang Zhou • Sayan Mukherjee	2018-03-12
Revisiting differentially private linear regression: optimal and adaptive prediction & estimation in unbounded domain \| Yu-Xiang Wang	2018-03-07
Missing Data in Sparse Transition Matrix Estimation for Sub-Gaussian Vector Autoregressive Processes Amin Jalali • Rebecca Willett	2018-02-26
Spatially Constrained Location Prior for Scene Parsing Ligang Zhang • Brijesh Verma • David Stockwell • Sujan Chowdhury	2018-02-24
Learning Mixtures of Linear Regressions with Nearly Optimal Complexity Yuanzhi Li • Yingyu Liang	2018-02-22
On the Optimization of Deep Networks: Implicit Acceleration by Overparameterization Sanjeev Arora • Nadav Cohen • Elad Hazan	2018-02-19
Leveraged volume sampling for linear regression Michał Dereziński • Manfred K. Warmuth • Daniel Hsu	2018-02-19
Articulatory information and Multiview Features for Large Vocabulary Continuous Speech Recognition Vikramjit Mitra • Wen Wang • Chris Bartels • Horacio Franco • Dimitra Vergyri	2018-02-16
Gradient Boosting With Piece-Wise Linear Regression Trees Yu Shi • Jian Li • Zhize Li	2018-02-15
Curriculum Learning by Transfer Learning: Theory and Experiments with Deep Networks Daphna Weinshall • Gad Cohen • Dan Amir	2018-02-11
Robust and Sparse Regression in GLM by Stochastic Optimization Takayuki Kawashima • Hironori Fujisawa	2018-02-09
Smart energy management as a means towards improved energy efficiency Dylan te Lindert • Cláudio Rebelo de Sá • Carlos Soares • Arno J. Knobbe	2018-02-08
On the Generalizability of Linear and Non-Linear Region of Interest-Based Multivariate Regression Models for fMRI Data Ethan C. Jackson • James Alexander Hughes • Mark Daley	2018-02-03
Using probabilistic programs as proposals Marco F. Cusumano-Towner • Vikash K. Mansinghka	2018-01-11
Least Square Error Method Robustness of Computation: What is not usually considered and taught Vaclav Skala	2018-01-01
Estimating activity cycles with probabilistic methods I. Bayesian Generalised Lomb-Scargle Periodogram with Trend N. Olspert • J. Pelt • M. J. Käpylä • J. Lehtinen	2017-12-21
Accurate Inference for Adaptive Linear Models Yash Deshpande • Lester Mackey • Vasilis Syrgkanis • Matt Taddy	2017-12-18
A Mathematical Programming Approach for Integrated Multiple Linear Regression Subset Selection and Validation Seokhyun Chung • Young Woong Park • Taesu Cheong	2017-12-12
Predicting Yelp Star Reviews Based on Network Structure with Deep Learning Luis Perez	2017-12-11
Multiple Adaptive Bayesian Linear Regression for Scalable Bayesian Optimization with Warm Start Valerio Perrone • Rodolphe Jenatton • Matthias Seeger • Cedric Archambeau	2017-12-08
Scaling Limit: Exact and Tractable Analysis of Online Learning Algorithms with Applications to Regularized Regression and PCA Chuang Wang • Jonathan Mattingly • Yue M. Lu	2017-12-08
High-dimensional robust regression and outliers detection with SLOPE Alain Virouleau • Agathe Guilloux • Stéphane Gaïffas • Malgorzata Bogdan	2017-12-07
CYUT at IJCNLP-2017 Task 3: System Report for Review Opinion Diversification Shih-Hung Wu • Su-Yu Chang • Liang-Pu Chen	2017-12-01
Best Response Regression Omer Ben-Porat • Moshe Tennenholtz	2017-12-01
Consistent Robust Regression Kush Bhatia • Prateek Jain • Parameswaran Kamalaruban • Purushottam Kar	2017-12-01
Efficient Sublinear-Regret Algorithms for Online Sparse Linear Regression with Limited Observation Shinji Ito • Daisuke Hatano • Hanna Sumita • Akihiro Yabe • Takuro Fukunaga • Naonori Kakimura • Ken-Ichi Kawarabayashi	2017-12-01
Valid Inference Corrected for Outlier Removal \| Shuxiao Chen • Jacob Bien	2017-11-29
Dependent relevance determination for smooth and structured sparse regression Anqi Wu • Oluwasanmi Koyejo • Jonathan W. Pillow	2017-11-28
Wisdom of the crowd from unsupervised dimension reduction Lingfei Wang • Tom Michoel	2017-11-28
On Breast Cancer Detection: An Application of Machine Learning Algorithms on the Wisconsin Diagnostic Dataset \| Abien Fred Agarap	2017-11-20
Discriminant Projection Representation-based Classification for Vision Recognition Qingxiang Feng • Yicong Zhou	2017-11-19
Sparse High-Dimensional Linear Regression. Algorithmic Barriers and a Local Search Algorithm David Gamarnik • Ilias Zadik	2017-11-14
Quadratic Programming Over Ellipsoids (with Applications to Constrained Linear Regression and Tensor Decomposition) Anh-Huy Phan • Masao Yamagishi • Danilo Mandic • Andrzej Cichocki	2017-11-13
Approximate message passing for nonconvex sparse regularization with stability and asymptotic analysis Ayaka Sakata • Yingying Xu	2017-11-08
Auto-Differentiating Linear Algebra Matthias Seeger • Asmus Hetzel • Zhenwen Dai • Eric Meissner • Neil D. Lawrence	2017-10-24
Facial Keypoints Detection Shenghao Shi	2017-10-15
$α$-Variational Inference with Statistical Guarantees Yun Yang • Debdeep Pati • Anirban Bhattacharya	2017-10-09
Clickbait detection using word embeddings Vijayasaradhi Indurthi • Subba Reddy Oota	2017-10-08
Weighted-SVD: Matrix Factorization with Weights on the Latent Factors \| Hung-Hsuan Chen	2017-10-02
Analytic solution and stationary phase approximation for the Bayesian lasso and elastic net \| Tom Michoel	2017-09-25
On Principal Components Regression, Random Projections, and Column Subsampling Martin Slawski	2017-09-23
Weighted Orthogonal Components Regression Analysis Xiaogang Su • Yaa Wonkye • Pei Wang • Xiangrong Yin	2017-09-13
Optimal Sub-sampling with Influence Functions Daniel Ting • Eric Brochu	2017-09-06
Adaptive Scaling Ting Li • Bingyi Jing • Ningchen Ying • Xianshi Yu	2017-09-02
DMGroup at EmoInt-2017: Emotion Intensity Using Ensemble Method Song Jiang • Xiaotian Han	2017-09-01
The Trimmed Lasso: Sparsity and Robustness \| Dimitris Bertsimas • Martin S. Copenhaver • Rahul Mazumder	2017-08-15
Attentional Factorization Machines: Learning the Weight of Feature Interactions via Attention Networks \| Jun Xiao • Hao Ye • Xiangnan He • Hanwang Zhang • Fei Wu • Tat-Seng Chua	2017-08-15
Generalized Meta-Analysis for Multiple Regression Models Across Studies with Disparate Covariate Information Prosenjit Kundu • Runlong Tang • Nilanjan Chatterjee	2017-08-12
GlobeNet: Convolutional Neural Networks for Typhoon Eye Tracking from Remote Sensing Imagery Seungkyun Hong • Seongchan Kim • Minsu Joh • Sa-kwang Song	2017-08-11
MITRE at SemEval-2017 Task 1: Simple Semantic Similarity John Henderson • Elizabeth Merkhofer • Laura Strickhart • Guido Zarrella	2017-08-01
UW-FinSent at SemEval-2017 Task 5: Sentiment Analysis on Financial News Headlines using Training Dataset Augmentation \| Vineet John • Olga Vechtomova	2017-08-01
DUTH at SemEval-2017 Task 5: Sentiment Predictability in Financial Microblogging and News Articles Symeon Symeonidis • John Kordonis • Dimitrios Effrosynidis • Avi Arampatzis	2017-08-01
Interpatient Respiratory Motion Model Transfer for Virtual Reality Simulations of Liver Punctures Andre Mastmeyer • Matthias Wilms • Heinz Handels	2017-07-26
Restricted Eigenvalue from Stable Rank with Applications to Sparse Linear Regression Shiva Prasad Kasiviswanathan • Mark Rudelson	2017-07-25
Tailoring Artificial Neural Networks for Optimal Learning \| Pau Vilimelis Aceituno • Yan Gang • Yang-Yu Liu	2017-07-08
Linguistic analysis of differences in portrayal of movie characters Anil Ramakrishna • Victor R. Mart{\'\i}nez • Mal • Nikolaos rakis • Karan Singla • Shrikanth Narayanan	2017-07-01
Asymptotic Confidence Regions for High-dimensional Structured Sparsity Benjamin Stucky • Sara van de Geer	2017-06-28
Top-down Transformation Choice Torsten Hothorn	2017-06-26
Adaptive Feature Selection: Computationally Efficient Online Sparse Linear Regression under RIP Satyen Kale • Zohar Karnin • Tengyuan Liang • Dávid Pál	2017-06-14
Collect at Once, Use Effectively: Making Non-interactive Locally Private Learning Possible Kai Zheng • Wenlong Mou • Liwei Wang	2017-06-11
A Robust Learning Algorithm for Regression Models Using Distributionally Robust Optimization under the Wasserstein Metric Ruidi Chen • Ioannis Ch. Paschalidis	2017-06-07
Exact adaptive confidence intervals for linear regression coefficients Peter D. Hoff • Chaoyu Yu	2017-05-23
Maximum Margin Principal Components Xianghui Luo • Robert J. Durrant	2017-05-17
Distributed Statistical Machine Learning in Adversarial Settings: Byzantine Gradient Descent Yudong Chen • Lili Su • Jiaming Xu	2017-05-16
Mind the Gap: A Well Log Data Analysis Rui L. Lopes • Alípio Jorge	2017-05-10
Linear Regression with Shuffled Labels Abubakar Abid • Ada Poon • James Zou	2017-05-03
Structured Sparse Modelling with Hierarchical GP Danil Kuzin • Olga Isupova • Lyudmila Mihaylova	2017-04-27
A Flexible Framework for Hypothesis Testing in High-dimensions Adel Javanmard • Jason D. Lee	2017-04-26
Denoising Linear Models with Permuted Data Ashwin Pananjady • Martin J. Wainwright • Thomas A. Courtade	2017-04-24
Solar Power Forecasting Using Support Vector Regression Mohamed Abuella • Badrul Chowdhury	2017-03-29
Multivariate Regression with Gross Errors on Manifold-valued Data Xiaowei Zhang • Xudong Shi • Yu Sun • Li Cheng	2017-03-26
Cross-Validation with Confidence \| Jing Lei	2017-03-23
Alternating optimization for GxE modelling with weighted genetic and environmental scores: examples from the MAVAN study Alexia Jolicoeur-Martineau • Ashley Wazana • Eszter Szekely • Meir Steiner • Alison S. Fleming • James L. Kennedy • Michael J. Meaney • Celia M. T. Greenwood	2017-03-23
Tuning Free Orthogonal Matching Pursuit Sreejith Kallummil • Sheetal Kalyani	2017-03-15
Fuzzy Model Tree For Early Effort Estimation Mohammad Azzeh • Ali Bou Nassif	2017-03-11
Memory-Efficient Global Refinement of Decision-Tree Ensembles and its Application to Face Alignment Nenad Markuš • Ivan Gogić • Igor S. Pandžić • Jörgen Ahlberg	2017-02-27
SAGA and Restricted Strong Convexity Chao Qu • Yan Li • Huan Xu	2017-02-19
Machine learning prediction errors better than DFT accuracy Felix A. Faber • Luke Hutchison • Bing Huang • Justin Gilmer • Samuel S. Schoenholz • George E. Dahl • Oriol Vinyals • Steven Kearnes • Patrick F. Riley • O. Anatole von Lilienfeld # 11 FORMATION ENERGY ON QM9	2017-02-17
Rate Optimal Estimation and Confidence Intervals for High-dimensional Regression with Missing Covariates Yining Wang • Jialei Wang • Sivaraman Balakrishnan • Aarti Singh	2017-02-09
On SGD's Failure in Practice: Characterizing and Overcoming Stalling Vivak Patel	2017-02-01
Subset Selection for Multiple Linear Regression via Optimization Young Woong Park • Diego Klabjan	2017-01-27
Identifying Nonlinear 1-Step Causal Influences in Presence of Latent Variables Saber Salehkaleybar • Jalal Etesami • Negar Kiyavash	2017-01-23
Efficient and Adaptive Linear Regression in Semi-Supervised Settings Abhishek Chakrabortty • Tianxi Cai	2017-01-17
High-Dimensional Regression with Binary Coefficients. Estimating Squared Error and a Phase Transition David Gamarnik • Ilias Zadik	2017-01-16
Symbolic Regression Algorithms with Built-in Linear Regression Jan Žegklitz • Petr Pošík	2017-01-13
Multivariate Regression with Grossly Corrupted Observations: A Robust Approach and its Applications Xiaowei Zhang • Chi Xu • Yu Zhang • Tingshao Zhu • Li Cheng	2017-01-11
Smart Content Recognition from Images Using a Mixture of Convolutional Neural Networks \| Tee Connie • Mundher Al-Shabi • Michael Goh	2016-12-30
Geometric descent method for convex composite minimization Shixiang Chen • Shiqian Ma • Wei Liu	2016-12-29
A Convex Program for Mixed Linear Regression with a Recovery Guarantee for Well-Separated Data Paul Hand • Babhru Joshi	2016-12-19
Measuring the non-asymptotic convergence of sequential Monte Carlo samplers using probabilistic programming Marco F. Cusumano-Towner • Vikash K. Mansinghka	2016-12-07
Combinatorial semi-bandit with known covariance Rémy Degenne • Vianney Perchet	2016-12-06
A Recurrent and Compositional Model for Personality Trait Recognition from Short Texts Fei Liu • Julien Perez • Scott Nowson	2016-12-01
CogALex-V Shared Task: GHHH - Detecting Semantic Relations via Word Embeddings Mohammed Attia • Suraj Maharjan • Younes Samih • Laura Kallmeyer • Thamar Solorio	2016-12-01
Predictability of Distributional Semantics in Derivational Word Formation Sebastian Pad{\'o} • Aur{\'e}lie Herbelot • Max Kisselew • Jan {\v{S}}najder	2016-12-01
GAP Safe Screening Rules for Sparse-Group Lasso \| Eugene Ndiaye • Olivier Fercoq • Alexandre Gramfort • Joseph Salmon	2016-12-01
A Bandit Framework for Strategic Regression Yang Liu • Yiling Chen	2016-12-01
Mixed Linear Regression with Multiple Components Kai Zhong • Prateek Jain • Inderjit S. Dhillon	2016-12-01
The Limits of Learning with Missing Data Brian Bullins • Elad Hazan • Tomer Koren	2016-12-01
Scalable Approximations for Generalized Linear Problems Murat A. Erdogdu • Mohsen Bayati • Lee H. Dicker	2016-11-21
Convolutional Regression for Visual Tracking Kai Chen • Wenbing Tao	2016-11-14
Unsupervised Learning For Effective User Engagement on Social Media Thai Pham • Camelia Simoiu	2016-11-11
Adaptive regularization for Lasso models in the context of non-stationary data streams Ricardo Pio Monti • Christoforos Anagnostopoulos • Giovanni Montana	2016-10-28
A Language-independent and Compositional Model for Personality Trait Recognition from Short Texts Fei Liu • Julien Perez • Scott Nowson	2016-10-14
A Study on Estimating the Next Failure Time of Compressor Equipment in an Offshore Plant SangJe Cho • Jong-Ho Shin • Hong-Bae Jun • Ho-Jin Hwang • Chunghun Ha • Jinsang Hwang	2016-10-03
On Randomized Distributed Coordinate Descent with Quantized Updates Mostafa El Gamal • Lifeng Lai	2016-09-18
Online Feature Selection with Group Structure Analysis Jing Wang • Meng Wang • Peipei Li • Luoqi Liu • Zhongqiu Zhao • Xuegang Hu • Xindong Wu	2016-08-21
Conditional Sparse Linear Regression Brendan Juba	2016-08-18
Variational Mixture Models with Gamma or inverse-Gamma components \| A. Llera • D. Vidaurre • R. H. R. Pruim • C. F. Beckmann	2016-07-26
Algorithms for Generalized Cluster-wise Linear Regression Young Woong Park • Yan Jiang • Diego Klabjan • Loren Williams	2016-07-05
Group Sparse Regularization for Deep Neural Networks Simone Scardapane • Danilo Comminiello • Amir Hussain • Aurelio Uncini	2016-07-02
Semi-supervised structured output prediction by local linear regression and sub-gradient descent Ru-Ze Liang • Wei Xie • Weizhi Li • Xin Du • Jim Jing-Yan Wang • Jingbin Wang	2016-06-07
PAC-Bayesian Theory Meets Bayesian Inference Pascal Germain • Francis Bach • Alexandre Lacoste • Simon Lacoste-Julien	2016-05-27
Bayesian linear regression with Student-t assumptions Chaobing Song • Shu-Tao Xia	2016-04-15
Learning Hough Regression Models via Bridge Partial Least Squares for Object Detection Jianyu Tang • Hanzi Wang • Yan Yan	2016-03-26
On the exact recovery of sparse signals via conic relaxations Hongbo Dong	2016-03-15
Template Matching via Densities on the Roto-Translation Group Erik J. Bekkers • Marco Loog • Bart M. ter Haar Romeny • Remco Duits	2016-03-10
Online Sparse Linear Regression Dean Foster • Satyen Kale • Howard Karloff	2016-03-07
Lasso estimation for GEFCom2014 probabilistic electric load forecasting Florian Ziel • Bidong Liu	2016-03-04
GAP Safe Screening Rules for Sparse-Group-Lasso \| Eugene Ndiaye • Olivier Fercoq • Alexandre Gramfort • Joseph Salmon	2016-02-19
The knockoff filter for FDR control in group-sparse and multitask regression Ran Dai • Rina Foygel Barber	2016-02-11
Online Active Linear Regression via Thresholding Carlos Riquelme • Ramesh Johari • Baosen Zhang	2016-02-09
A Robust UCB Scheme for Active Learning in Regression from Strategic Crowds Divya Padmanabhan • Satyanath Bhat • Dinesh Garg • Shirish Shevade • Y. Narahari	2016-01-25
ActiveClean: Interactive Data Cleaning While Learning Convex Loss Models Sanjay Krishnan • Jiannan Wang • Eugene Wu • Michael J. Franklin • Ken Goldberg	2016-01-15
On Computationally Tractable Selection of Experiments in Measurement-Constrained Regression Models Yining Wang • Adams Wei Yu • Aarti Singh	2016-01-09
On the Differential Privacy of Bayesian Inference Zuhe Zhang • Benjamin Rubinstein • Christos Dimitrakakis	2015-12-22
Selective Sequential Model Selection William Fithian • Jonathan Taylor • Robert Tibshirani • Ryan Tibshirani	2015-12-08
Random Forests for Big Data Robin Genuer • Jean-Michel Poggi • Christine Tuleau-Malot • Nathalie Villa-Vialaneix	2015-11-26
Optimized Linear Imputation Yehezkel S. Resheff • Daphna Weinshall	2015-11-17
Lass-0: sparse non-convex regression by local search William Herlands • Maria De-Arteaga • Daniel Neill • Artur Dubrawski	2015-11-13
Streaming regularization parameter selection via stochastic gradient descent Ricardo Pio Monti • Romy Lorenz • Robert Leech • Christoforos Anagnostopoulos • Giovanni Montana	2015-11-06
On the complexity of switching linear regression Fabien Lauer	2015-10-23
Decadal climate predictions using sequential learning algorithms Ehud Strobach • Golan Bel	2015-09-17
Bayesian Masking: Sparse Bayesian Estimation with Weaker Shrinkage Bias Yohei Kondo • Kohei Hayashi • Shin-ichi Maeda	2015-09-03
A Gibbs Sampler for Multivariate Linear Regression Adam B. Mantz	2015-09-03
Online Supervised Subspace Tracking Yao Xie • Ruiyang Song • Hanjun Dai • Qingbin Li • Le Song	2015-09-01
A Comparison Between Decision Trees and Decision Tree Forest Models for Software Development Effort Estimation Ali Bou Nassif • Mohammad Azzeh • Luiz Fernando Capretz • Danny Ho	2015-08-28
The Discrete Dantzig Selector: Estimating Sparse Linear Models via Mixed Integer Linear Optimization Rahul Mazumder • Peter Radchenko	2015-08-08
Robust and sparse estimators for linear regression models Ezequiel Smucler • Víctor J. Yohai	2015-08-08
Best Subset Selection via a Modern Optimization Lens Dimitris Bertsimas • Angela King • Rahul Mazumder	2015-07-11
Differentially Private Ordinary Least Squares Or Sheffet	2015-07-09
Portfolio optimization using local linear regression ensembles in RapidMiner Gabor Nagy • Gergo Barta • Tamas Henk	2015-06-29
Modality-dependent Cross-media Retrieval Yunchao Wei • Yao Zhao • Zhenfeng Zhu • Shikui Wei • Yanhui Xiao • Jiashi Feng • Shuicheng Yan	2015-06-22
On the Computational Complexity of High-Dimensional Bayesian Variable Selection Yun Yang • Martin J. Wainwright • Michael I. Jordan	2015-05-29
Supervised Learning for Dynamical System Learning Ahmed Hefny • Carlton Downey • Geoffrey Gordon	2015-05-20
A New Perspective on Boosting in Linear Regression via Subgradient Optimization and Relatives Robert M. Freund • Paul Grigas • Rahul Mazumder	2015-05-16
Linearly Supporting Feature Extraction For Automated Estimation Of Stellar Atmospheric Parameters Xiangru Li • Yu Lu • Georges Comte • Ali Luo • Yongheng Zhao • Yongjun Wang	2015-04-09
Asymmetric Distributions from Constrained Mixtures Conrado S. Miranda • Fernando J. Von Zuben	2015-03-22
Nonparametric Detection of Nonlinearly Mixed Pixels and Endmember Estimation in Hyperspectral Images Tales Imbiriba • José Carlos Moreira Bermudez • Cédric Richard • Jean-Yves Tourneret	2015-03-18
Improved Calibration of Near-Infrared Spectra by Using Ensembles of Neural Network Models A. Ukil • J. Bernasconi • H. Braendle • H. Buijs • S. Bonenfant	2015-03-18
Maximum a Posteriori Adaptation of Network Parameters in Deep Models Zhen Huang • Sabato Marco Siniscalchi • I-Fan Chen • Jiadong Wu • Chin-Hui Lee	2015-03-06
Finding Dantzig selectors with a proximity operator based fixed-point algorithm Ashley Prater • Lixin Shen • Bruce W. Suter	2015-02-19
Per-Block-Convex Data Modeling by Accelerated Stochastic Approximation Konstantinos Slavakis • Georgios B. Giannakis	2015-01-29
Minimax Optimal Sparse Signal Recovery with Poisson Statistics Mohammad H. Rohban • Delaram Motamedvaziri • Venkatesh Saligrama	2015-01-21
Separation of undersampled composite signals using the Dantzig selector with overcomplete dictionaries Ashley Prater • Lixin Shen	2015-01-20
Implementable confidence sets in high dimensional regression Alexandra Carpentier	2015-01-19
HyperSpectral classification with adaptively weighted L1-norm regularization and spatial postprocessing Victor Stefan Aldea	2014-12-08
Sparse Bayesian structure learning with “dependent relevance determination” priors Anqi Wu • Mijung Park • Oluwasanmi O. Koyejo • Jonathan W. Pillow	2014-12-01
On Sparse Gaussian Chain Graph Models Calvin Mccarter • Seyoung Kim	2014-12-01
Distributed Bayesian Posterior Sampling via Moment Sharing Minjie Xu • Balaji Lakshminarayanan • Yee Whye Teh • Jun Zhu • Bo Zhang	2014-12-01
Private Empirical Risk Minimization Beyond the Worst Case: The Effect of the Constraint Set Geometry \| Kunal Talwar • Abhradeep Thakurta • Li Zhang	2014-11-20
Multivariate response and parsimony for Gaussian cluster-weighted models Utkarsh J. Dang • Antonio Punzo • Paul D. McNicholas • Salvatore Ingrassia • Ryan P. Browne	2014-11-03
Population Empirical Bayes \| Alp Kucukelbir • David M. Blei	2014-11-02
On Iterative Hard Thresholding Methods for High-dimensional M-Estimation Prateek Jain • Ambuj Tewari • Purushottam Kar	2014-10-20
Augmented Neural Networks for Modelling Consumer Indebtness Alexandros Ladas • Jonathan M. Garibaldi • Rodrigo Scarpel • Uwe Aickelin	2014-09-03
Large Scale Purchase Prediction with Historical User Actions on B2C Online Retail Platform Yuyu Zhang • Liang Pang • Lei Shi • Bin Wang	2014-08-27
Statistical guarantees for the EM algorithm: From population to sample-based analysis Sivaraman Balakrishnan • Martin J. Wainwright • Bin Yu	2014-08-09
RAPID: Rapidly Accelerated Proximal Gradient Algorithms for Convex Minimization Ziming Zhang • Venkatesh Saligrama	2014-06-13
Discriminative Functional Connectivity Measures for Brain Decoding Orhan Firat • Mete Ozay • Ilke Oztekin • Fatos T. Yarman Vural	2014-02-23
Retrieval of Experiments by Efficient Estimation of Marginal Likelihood Sohan Seth • John Shawe-Taylor • Samuel Kaski	2014-02-19
Monte Carlo Simulation for Lasso-Type Problems by Estimator Augmentation Qing Zhou	2014-01-17
Use Case Point Approach Based Software Effort Estimation using Various Support Vector Regression Kernel Methods Shashank Mouli Satapathy • Santanu Kumar Rath	2014-01-14
Inference in High Dimensions with the Penalized Score Test Arend Voorman • Ali Shojaie • Daniela Witten	2014-01-12
Learning optimization models in the presence of unknown relations Sicco Verwer • Yingqian Zhang • Qing Chuan Ye	2014-01-06
Unsupervised Discovery of Biographical Structure from Text David Bamman • Noah A. Smith	2014-01-01
Supervised learning of a regression model based on latent process. Application to the estimation of fuel cell life time Raïssa Onanena • Faicel Chamroukhi • Latifa Oukhellou • Denis Candusso • Patrice Aknin • Daniel Hissel	2013-12-25
Modèle à processus latent et algorithme EM pour la régression non linéaire Faicel Chamroukhi • Allou Samé • Gérard Govaert • Patrice Aknin	2013-12-25
Performance Analysis Of Regularized Linear Regression Models For Oxazolines And Oxazoles Derivitive Descriptor Dataset Doreswamy • Chanabasayya . M. Vastrad	2013-12-10
Swapping Variables for High-Dimensional Sparse Regression with Correlated Measurements Divyanshu Vats • Richard G. Baraniuk	2013-12-05
Information-theoretic lower bounds for distributed statistical estimation with communication constraints Yuchen Zhang • John Duchi • Michael I. Jordan • Martin J. Wainwright	2013-12-01
A Comprehensive Approach to Universal Piecewise Nonlinear Regression Based on Trees N. Denizcan Vanli • Suleyman S. Kozat	2013-11-25
When Does More Regularization Imply Fewer Degrees of Freedom? Sufficient Conditions and Counter Examples from Lasso and Ridge Regression Shachar Kaufman • Saharon Rosset	2013-11-12
Regularization of $\ell_1$ minimization for dealing with outliers and noise in Statistics and Signal Recovery Salvador Flores • Luis M. Briceno-Arias	2013-10-28
Alternating Minimization for Mixed Linear Regression Xinyang Yi • Constantine Caramanis • Sujay Sanghavi	2013-10-14
Linear Regression from Strategic Data Sources Nicolas Gast • Stratis Ioannidis • Patrick Loiseau • Benjamin Roussillon	2013-09-30
Learning from the past, predicting the statistics for the future, learning an evolving system Daniel Levin • Terry Lyons • Hao Ni	2013-09-01
Confidence Sets Based on Thresholding Estimators in High-Dimensional Gaussian Regression Models Ulrike Schneider	2013-08-14
Sharp Threshold for Multivariate Multi-Response Linear Regression via Block Regularized Lasso Weiguang Wang • Yingbin Liang • Eric P. Xing	2013-07-30
Loss minimization and parameter estimation with heavy tails Daniel Hsu • Sivan Sabato	2013-07-07
A Statistical Perspective on Algorithmic Leveraging Ping Ma • Michael W. Mahoney • Bin Yu	2013-06-23
Spectral Experts for Estimating Mixtures of Linear Regressions Arun Tejasvi Chaganty • Percy Liang	2013-06-17
Confidence Intervals and Hypothesis Testing for High-Dimensional Regression Adel Javanmard • Andrea Montanari	2013-06-13
Analytic Feature Selection for Support Vector Machines Carly Stambaugh • Hui Yang • Felix Breuer	2013-04-20
Distributed dictionary learning over a sensor network Pierre Chainais • Cédric Richard	2013-04-12
Feature Multi-Selection among Subjective Features Sivan Sabato • Adam Kalai	2013-02-18
A significance test for the lasso Richard Lockhart • Jonathan Taylor • Ryan J. Tibshirani • Robert Tibshirani	2013-01-30
Hypothesis Testing in High-Dimensional Regression under the Gaussian Random Design Model: Asymptotic Theory Adel Javanmard • Andrea Montanari	2013-01-17
Optimal classification in sparse Gaussian graphic model Yingying Fan • Jiashun Jin • Zhigang Yao	2012-12-21
Fixed-rank matrix factorizations and Riemannian low-rank optimization B. Mishra • G. Meyer • S. Bonnabel • R. Sepulchre	2012-09-03
Optimality of Graphlet Screening in High Dimensional Variable Selection Jiashun Jin • Cun-Hui Zhang • Qi Zhang	2012-04-29
Adaptive and optimal online linear regression on $\ell^1$-balls Sébastien Gerchinovitz • Jia Yuan Yu	2011-05-20
Sparsity regret bounds for individual sequences in online linear regression Sébastien Gerchinovitz	2011-01-05
Fast global convergence rates of gradient methods for high-dimensional statistical recovery Alekh Agarwal • Sahand Negahban • Martin J. Wainwright	2010-12-01
Parametric Bandits: The Generalized Linear Case Sarah Filippi • Olivier Cappe • Aurélien Garivier • Csaba Szepesvári	2010-12-01
A Dirty Model for Multi-task Learning Ali Jalali • Sujay Sanghavi • Chao Ruan • Pradeep K. Ravikumar	2010-12-01
A Family of Penalty Functions for Structured Sparsity Jean Morales • Charles A. Micchelli • Massimiliano Pontil	2010-12-01
Directed Regression Yi-Hao Kao • Benjamin V. Roy • Xiang Yan	2009-12-01
Heterogeneous multitask learning with joint sparsity constraints Xiaolin Yang • Seyoung Kim • Eric P. Xing	2009-12-01
A Fast Algorithm for Robust Regression with Penalised Trimmed Squares L. Pitsoulis • G. Zioutas	2009-01-07
Modeling human function learning with Gaussian processes Thomas L. Griffiths • Chris Lucas • Joseph Williams • Michael L. Kalish	2008-12-01
Phase transitions for high-dimensional joint support recovery Sahand Negahban • Martin J. Wainwright	2008-12-01
Bolasso: model consistent Lasso estimation through the bootstrap \| Francis Bach	2008-04-08
Online Linear Regression and Its Application to Model-Based Reinforcement Learning Alexander L. Strehl • Michael L. Littman	2007-12-01
Spike and slab variable selection: Frequentist and Bayesian strategies Hemant Ishwaran • J. Sunil Rao	2005-05-30

Tasks

TASK	PAPERS	SHARE
Time Series	15	6.76%
Feature Selection	8	3.60%
Active Learning	7	3.15%
Image Classification	7	3.15%
EEG	6	2.70%
Meta-Learning	6	2.70%
Imputation	6	2.70%
Feature Engineering	6	2.70%
Dimensionality Reduction	6	2.70%

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Generalized Linear Models