Search Results for author: Min Wu

Found 68 papers, 21 papers with code

Augmenting and Aligning Snippets for Few-Shot Video Domain Adaptation

no code implementations18 Mar 2023 Yuecong Xu, Jianfei Yang, Yunjiao Zhou, Zhenghua Chen, Min Wu, XiaoLi Li

We thus consider a more realistic \textit{Few-Shot Video-based Domain Adaptation} (FSVDA) scenario where we adapt video models with only a few target video samples.

Action Recognition Unsupervised Domain Adaptation

CoNIC Challenge: Pushing the Frontiers of Nuclear Detection, Segmentation, Classification and Counting

no code implementations11 Mar 2023 Simon Graham, Quoc Dang Vu, Mostafa Jahanifar, Martin Weigert, Uwe Schmidt, Wenhua Zhang, Jun Zhang, Sen yang, Jinxi Xiang, Xiyue Wang, Josef Lorenz Rumberger, Elias Baumann, Peter Hirsch, Lihao Liu, Chenyang Hong, Angelica I. Aviles-Rivero, Ayushi Jain, Heeyoung Ahn, Yiyu Hong, Hussam Azzuni, Min Xu, Mohammad Yaqub, Marie-Claire Blache, Benoît Piégu, Bertrand Vernay, Tim Scherr, Moritz Böhland, Katharina Löffler, Jiachen Li, Weiqin Ying, Chixin Wang, Dagmar Kainmueller, Carola-Bibiane Schönlieb, Shuolin Liu, Dhairya Talsania, Yughender Meda, Prakash Mishra, Muhammad Ridzuan, Oliver Neumann, Marcel P. Schilling, Markus Reischl, Ralf Mikut, Banban Huang, Hsiang-Chin Chien, Ching-Ping Wang, Chia-Yen Lee, Hong-Kun Lin, Zaiyi Liu, Xipeng Pan, Chu Han, Jijun Cheng, Muhammad Dawood, Srijay Deshpande, Raja Muhammad Saad Bashir, Adam Shephard, Pedro Costa, João D. Nunes, Aurélio Campilho, Jaime S. Cardoso, Hrishikesh P S, Densen Puthussery, Devika R G, Jiji C V, Ye Zhang, Zijie Fang, Zhifan Lin, Yongbing Zhang, Chunhui Lin, Liukun Zhang, Lijian Mao, Min Wu, Vi Thi-Tuong Vo, Soo-Hyung Kim, Taebum Lee, Satoshi Kondo, Satoshi Kasai, Pranay Dumbhare, Vedant Phuse, Yash Dubey, Ankush Jamthikar, Trinh Thi Le Vuong, Jin Tae Kwak, Dorsa Ziaei, Hyun Jung, Tianyi Miao, David Snead, Shan E Ahmed Raza, Fayyaz Minhas, Nasir M. Rajpoot

Nuclear detection, segmentation and morphometric profiling are essential in helping us further understand the relationship between histology and patient outcome.

Nuclear Segmentation Survival Analysis +1

MetaGrad: Adaptive Gradient Quantization with Hypernetworks

no code implementations4 Mar 2023 Kaixin Xu, Alina Hui Xiu Lee, Ziyuan Zhao, Zhe Wang, Min Wu, Weisi Lin

A popular track of network compression approach is Quantization aware Training (QAT), which accelerates the forward pass during the neural network training and inference.


Convex Bounds on the Softmax Function with Applications to Robustness Verification

1 code implementation3 Mar 2023 Dennis Wei, Haoze Wu, Min Wu, Pin-Yu Chen, Clark Barrett, Eitan Farchi

The softmax function is a ubiquitous component at the output of neural networks and increasingly in intermediate layers as well.

Data-Centric AI: Deep Generative Differentiable Feature Selection via Discrete Subsetting as Continuous Embedding Space Optimization

no code implementations26 Feb 2023 Meng Xiao, Dongjie Wang, Min Wu, Pengfei Wang, Yuanchun Zhou, Yanjie Fu

We generalize this problem into a deep differentiable feature selection task and propose a new perspective: discrete feature subsetting as continuous embedding space optimization.

Label-efficient Time Series Representation Learning: A Review

no code implementations13 Feb 2023 Emadeldeen Eldele, Mohamed Ragab, Zhenghua Chen, Min Wu, Chee-Keong Kwoh, XiaoLi Li

The scarcity of labeled data is one of the main challenges of applying deep learning models on time series data in the real world.

Representation Learning Self-Supervised Learning +2

Spatially informed clustering, integration, and deconvolution of spatial transcriptomics with GraphST

no code implementations bioRxiv 2023 Yahui Long, Kok Siong Ang, Mengwei Li, Kian Long Kelvin Chong, Raman Sethi, Chengwei Zhong, Hang Xu, Zhiwei Ong, Karishma Sachaphibulkij, Ao Chen, Zeng Li, Huazhu Fu, Min Wu, Hsiu Kim Lina Lim, Longqi Liu, Jinmiao Chen

Lastly, compared to other methods, GraphST’s cell type deconvolution achieved higher accuracy on simulated data and better captured spatial niches such as the germinal centers of the lymph node in experimentally acquired data.

Contrastive Learning

Traceable Automatic Feature Transformation via Cascading Actor-Critic Agents

1 code implementation27 Dec 2022 Meng Xiao, Dongjie Wang, Min Wu, Ziyue Qiao, Pengfei Wang, Kunpeng Liu, Yuanchun Zhou, Yanjie Fu

Feature transformation for AI is an essential task to boost the effectiveness and interpretability of machine learning (ML).

On the Probability of Necessity and Sufficiency of Explaining Graph Neural Networks: A Lower Bound Optimization Approach

no code implementations14 Dec 2022 Ruichu Cai, Yuxuan Zhu, Xuexin Chen, Yuan Fang, Min Wu, Jie Qiao, Zhifeng Hao

To address the non-identifiability of PNS, we resort to a lower bound of PNS that can be optimized via counterfactual estimation, and propose Necessary and Sufficient Explanation for GNN (NSEG) via optimizing that lower bound.

CoTMix: Contrastive Domain Adaptation for Time-Series via Temporal Mixup

1 code implementation3 Dec 2022 Emadeldeen Eldele, Mohamed Ragab, Zhenghua Chen, Min Wu, Chee-Keong Kwoh, XiaoLi Li

Specifically, we propose a novel temporal mixup strategy to generate two intermediate augmented views for the source and target domains.

Contrastive Learning Time Series Analysis +1

VeriX: Towards Verified Explainability of Deep Neural Networks

no code implementations2 Dec 2022 Min Wu, Haoze Wu, Clark Barrett

We present VeriX, a system for producing optimal robust explanations and generating counterfactuals along decision boundaries of machine learning models.

Self-Optimizing Feature Transformation

no code implementations16 Sep 2022 Meng Xiao, Dongjie Wang, Min Wu, Kunpeng Liu, Hui Xiong, Yuanchun Zhou, Yanjie Fu

Feature transformation aims to extract a good representation (feature) space by mathematically transforming existing features.

Feature Engineering Outlier Detection

SwiftPruner: Reinforced Evolutionary Pruning for Efficient Ad Relevance

no code implementations30 Aug 2022 Li Lyna Zhang, Youkow Homma, Yujing Wang, Min Wu, Mao Yang, Ruofei Zhang, Ting Cao, Wei Shen

Remarkably, under our latency requirement of 1900us on CPU, SwiftPruner achieves a 0. 86% higher AUC than the state-of-the-art uniform sparse baseline for BERT-Mini on a large scale real-world dataset.

Self-supervised Contrastive Representation Learning for Semi-supervised Time-Series Classification

2 code implementations13 Aug 2022 Emadeldeen Eldele, Mohamed Ragab, Zhenghua Chen, Min Wu, Chee-Keong Kwoh, XiaoLi Li, Cuntai Guan

Specifically, we propose time-series specific weak and strong augmentations and use their views to learn robust temporal relations in the proposed temporal contrasting module, besides learning discriminative representations by our proposed contextual contrasting module.

Contrastive Learning Data Augmentation +4

Leveraging Endo- and Exo-Temporal Regularization for Black-box Video Domain Adaptation

no code implementations10 Aug 2022 Yuecong Xu, Jianfei Yang, Haozhi Cao, Min Wu, XiaoLi Li, Lihua Xie, Zhenghua Chen

To enable video models to be applied seamlessly across video tasks in different environments, various Video Unsupervised Domain Adaptation (VUDA) methods have been proposed to improve the robustness and transferability of video models.

Action Recognition Unsupervised Domain Adaptation

A Generalized Probabilistic Monitoring Model with Both Random and Sequential Data

no code implementations27 Jun 2022 Wanke Yu, Min Wu, Biao Huang, Chengda Lu

Many multivariate statistical analysis methods and their corresponding probabilistic counterparts have been adopted to develop process monitoring models in recent decades.

Multi-Omic Data Integration and Feature Selection for Survival-based Patient Stratification via Supervised Concrete Autoencoders

1 code implementation21 Jun 2022 Pedro Henrique da Costa Avelar, Roman Laddach, Sophia Karagiannis, Min Wu, Sophia Tsoka

We also perform a feature selection stability analysis on our models and notice that there is a power-law relationship with features which are commonly associated with survival.

Data Integration

Bispectrum-based Cross-frequency Functional Connectivity: Classification of Alzheimer's disease

no code implementations10 Jun 2022 Dominik Klepl, Fei He, Min Wu, Daniel J. Blackburn, Ptolemaios G. Sarrigiannis

Cross-bispectrum, a higher-order spectral analysis, is used to measure the nonlinear FC and is compared with the cross-spectrum, which only measures the linear FC within bands.

Classification Electroencephalogram (EEG)

A Survey on AI Sustainability: Emerging Trends on Learning Algorithms and Research Challenges

no code implementations8 May 2022 Zhenghua Chen, Min Wu, Alvin Chan, XiaoLi Li, Yew-Soon Ong

We believe that this technical review can help to promote a sustainable development of AI R&D activities for the research community.


Real-time Speech Emotion Recognition Based on Syllable-Level Feature Extraction

no code implementations25 Apr 2022 Abdul Rehman, Zhen-Tao Liu, Min Wu, Wei-Hua Cao, Cheng-Shan Jiang

A set of syllable-level formant features is extracted and fed into a single hidden layer neural network that makes predictions for each syllable as opposed to the conventional approach of using a sophisticated deep learner to make sentence-wide predictions.

Cross-corpus Speech Emotion Recognition

RadioSES: mmWave-Based Audioradio Speech Enhancement and Separation System

no code implementations14 Apr 2022 Muhammed Zahid Ozturk, Chenshu Wu, Beibei Wang, Min Wu, K. J. Ray Liu

Speech enhancement and separation have been a long-standing problem, especially with the recent advances using a single microphone.

Association Speech Enhancement +1

ADATIME: A Benchmarking Suite for Domain Adaptation on Time Series Data

1 code implementation15 Mar 2022 Mohamed Ragab, Emadeldeen Eldele, Wee Ling Tan, Chuan-Sheng Foo, Zhenghua Chen, Min Wu, Chee-Keong Kwoh, XiaoLi Li

Our evaluation includes adapting state-of-the-art visual domain adaptation methods to time series data in addition to the recent methods specifically developed for time series data.

Benchmarking Time Series Analysis +1

Separable-HoverNet and Instance-YOLO for Colon Nuclei Identification and Counting

no code implementations1 Mar 2022 Chunhui Lin, Liukun Zhang, Lijian Mao, Min Wu, Dong Hu

Nuclear segmentation, classification and quantification within Haematoxylin & Eosin stained histology images enables the extraction of interpretable cell-based features that can be used in downstream explainable models in computational pathology (CPath).

Classification Explainable Models +1

Lumbar Bone Mineral Density Estimation from Chest X-ray Images: Anatomy-aware Attentive Multi-ROI Modeling

no code implementations5 Jan 2022 Fakai Wang, Kang Zheng, Le Lu, Jing Xiao, Min Wu, Chang-Fu Kuo, Shun Miao

Osteoporosis is a common chronic metabolic bone disease often under-diagnosed and under-treated due to the limited access to bone mineral density (BMD) examinations, e. g. via Dual-energy X-ray Absorptiometry (DXA).

Anatomy Density Estimation

Motif Graph Neural Network

no code implementations30 Dec 2021 Xuexin Chen, Ruichu Cai, Yuan Fang, Min Wu, Zijian Li, Zhifeng Hao

However, standard GNNs in the neighborhood aggregation paradigm suffer from limited discriminative power in distinguishing \emph{high-order} graph structures as opposed to \emph{low-order} structures.

Graph Classification Graph Embedding +2

Self-supervised Autoregressive Domain Adaptation for Time Series Data

1 code implementation29 Nov 2021 Mohamed Ragab, Emadeldeen Eldele, Zhenghua Chen, Min Wu, Chee-Keong Kwoh, XiaoLi Li

Second, we propose a novel autoregressive domain adaptation technique that incorporates temporal dependency of both source and target features during domain alignment.

Self-Supervised Learning Time Series Analysis +1

A Systematic Evaluation of Domain Adaptation Algorithms On Time Series Data

no code implementations29 Sep 2021 Mohamed Ragab, Emadeldeen Eldele, Wee Ling Tan, Chuan-Sheng Foo, Zhenghua Chen, Min Wu, Chee Kwoh, XiaoLi Li

Our evaluation includes adaptations of state-of-the-art visual domain adaptation methods to time series data in addition to recent methods specifically developed for time series data.

Benchmarking Model Selection +2

Multi-Source Video Domain Adaptation with Temporal Attentive Moment Alignment

no code implementations21 Sep 2021 Yuecong Xu, Jianfei Yang, Haozhi Cao, Keyu Wu, Min Wu, Rui Zhao, Zhenghua Chen

Multi-Source Domain Adaptation (MSDA) is a more practical domain adaptation scenario in real-world scenarios.

Unsupervised Domain Adaptation

A Multi-Channel Ratio-of-Ratios Method for Noncontact Hand Video Based SpO2 Monitoring Using Smartphone Cameras

no code implementations18 Jul 2021 Xin Tian, Chau-Wai Wong, Sushant M. Ranadive, Min Wu

Experimental results show that our proposed blood oxygen estimation method can reach a mean absolute error of 1. 26% when a pulse oximeter is used as a reference, outperforming the traditional RoR method by 25%.

Remote Blood Oxygen Estimation From Videos Using Neural Networks

no code implementations11 Jul 2021 Joshua Mathew, Xin Tian, Min Wu, Chau-Wai Wong

Blood oxygen saturation (SpO$_2$) is an essential indicator of respiratory functionality and is receiving increasing attention during the COVID-19 pandemic.

ADAST: Attentive Cross-domain EEG-based Sleep Staging Framework with Iterative Self-Training

1 code implementation9 Jul 2021 Emadeldeen Eldele, Mohamed Ragab, Zhenghua Chen, Min Wu, Chee-Keong Kwoh, XiaoLi Li, Cuntai Guan

Second, we design an iterative self-training strategy to improve the classification performance on the target domain via target domain pseudo labels.

Automatic Sleep Stage Classification Domain Adaptation +1

Time-Series Representation Learning via Temporal and Contextual Contrasting

1 code implementation26 Jun 2021 Emadeldeen Eldele, Mohamed Ragab, Zhenghua Chen, Min Wu, Chee Keong Kwoh, XiaoLi Li, Cuntai Guan

In this paper, we propose an unsupervised Time-Series representation learning framework via Temporal and Contextual Contrasting (TS-TCC), to learn time-series representation from unlabeled data.

Automatic Sleep Stage Classification Contrastive Learning +8

Feasibility Study on Intra-Grid Location Estimation Using Power ENF Signals

no code implementations3 May 2021 Ravi Garg, Adi Hajj-Ahmad, Min Wu

In this study, we demonstrate that it is possible to pinpoint the location-of-recording to a certain geographical resolution using power signal recordings containing strong ENF traces.

An Attention-Based Deep Learning Approach for Sleep Stage Classification With Single-Channel EEG

1 code implementation28 Apr 2021 Emadeldeen Eldele, Zhenghua Chen, Chengyu Liu, Min Wu, Chee-Keong Kwoh, XiaoLi Li, Cuntai Guan

The MRCNN can extract low and high frequency features and the AFR is able to improve the quality of the extracted features by modeling the inter-dependencies between the features.

Automatic Sleep Stage Classification Electroencephalogram (EEG) +1

Opportunistic Screening of Osteoporosis Using Plain Film Chest X-ray

no code implementations5 Apr 2021 Fakai Wang, Kang Zheng, Yirui Wang, XiaoYun Zhou, Le Lu, Jing Xiao, Min Wu, Chang-Fu Kuo, Shun Miao

In this paper, we propose a method to predict BMD from Chest X-ray (CXR), one of the most common, accessible, and low-cost medical image examinations.

FFConv: Fast Factorized Convolutional Neural Network Inference on Encrypted Data

no code implementations6 Feb 2021 Yuxiao Lu, Jie Lin, Chao Jin, Zhe Wang, Min Wu, Khin Mi Mi Aung, XiaoLi Li

Despite the faster HECNN inference, the mainstream packing schemes Dense Packing (DensePack) and Convolution Packing (ConvPack) introduce expensive rotation overhead, which prolongs the inference latency of HECNN for deeper and wider CNN architectures.

Privacy Preserving

Cross-domain Joint Dictionary Learning for ECG Inference from PPG

no code implementations7 Jan 2021 Xin Tian, Qiang Zhu, Yuenan Li, Min Wu

The inverse problem of inferring electrocardiogram (ECG) from photoplethysmogram (PPG) is an emerging research direction that combines the easy measurability of PPG and the rich clinical knowledge of ECG for long-term continuous cardiac monitoring.

Clinical Knowledge Dictionary Learning

Automatic Vertebra Localization and Identification in CT by Spine Rectification and Anatomically-constrained Optimization

no code implementations CVPR 2021 Fakai Wang, Kang Zheng, Le Lu, Jing Xiao, Min Wu, Shun Miao

This paper proposes a robust and accurate method that effectively exploits the anatomical knowledge of the spine to facilitate vertebra localization and identification.

Inferring ECG from PPG for Continuous Cardiac Monitoring Using Lightweight Neural Network

no code implementations9 Dec 2020 Yuenan Li, Xin Tian, Qiang Zhu, Min Wu

It is also infeasible to expect persistently active user participation for long-term continuous cardiac monitoring in order to capture these and other types of abnormalities of the heart.

Model Compression

Attention Sequence to Sequence Model for Machine Remaining Useful Life Prediction

no code implementations20 Jul 2020 Mohamed Ragab, Zhenghua Chen, Min Wu, Chee-Keong Kwoh, Ruqiang Yan, Xiao-Li Li

Accurate estimation of remaining useful life (RUL) of industrial equipment can enable advanced maintenance schedules, increase equipment availability and reduce operational costs.

Recent Advances in Network-based Methods for Disease Gene Prediction

1 code implementation19 Jul 2020 Sezin Kircali Ata, Min Wu, Yuan Fang, Le Ou-Yang, Chee Keong Kwoh, Xiao-Li Li

Thirdly, an empirical analysis is conducted to evaluate the performance of the selected methods across seven diseases.

Association Graph Representation Learning

Transparency Tools for Fairness in AI (Luskin)

no code implementations9 Jul 2020 Mingliang Chen, Aria Shahverdi, Sarah Anderson, Se Yong Park, Justin Zhang, Dana Dachman-Soled, Kristin Lauter, Min Wu

The three tools are: - A new definition of fairness called "controlled fairness" with respect to choices of protected features and filters.


Towards Threshold Invariant Fair Classification

no code implementations18 Jun 2020 Mingliang Chen, Min Wu

This paper introduces the notion of threshold invariant fairness, which enforces equitable performances across different groups independent of the decision threshold.

BIG-bench Machine Learning Classification +2

Multi-View Collaborative Network Embedding

3 code implementations17 May 2020 Sezin Kircali Ata, Yuan Fang, Min Wu, Jiaqi Shi, Chee Keong Kwoh, Xiao-Li Li

Real-world networks often exist with multiple views, where each view describes one type of interaction among a common set of nodes.

Network Embedding

Adaptive Multi-Trace Carving for Robust Frequency Tracking in Forensic Applications

no code implementations14 May 2020 Qiang Zhu, Mingliang Chen, Chau-Wai Wong, Min Wu

In the field of information forensics, many emerging problems involve a critical step that estimates and tracks weak frequency components in noisy signals.

Contextualized Graph Attention Network for Recommendation with Item Knowledge Graph

no code implementations24 Apr 2020 Susen Yang, Yong liu, Yonghui Xu, Chunyan Miao, Min Wu, Juyong Zhang

Graph neural networks (GNN) have recently been applied to exploit knowledge graph (KG) for recommendation.

Graph Attention

Respiratory Rate Estimation from Face Videos

no code implementations8 Sep 2019 Mingliang Chen, Qiang Zhu, Harrison Zhang, Min Wu, Quanzeng Wang

Commercial cameras are promising contact-free sensors, and remote photoplethysmography (rPPG) have been studied to remotely monitor heart rate from face videos.

Heart Rate Variability Motion Compensation +1

A Deep Framework for Bone Age Assessment based on Finger Joint Localization

no code implementations7 May 2019 Xiaoman Zhang, Ziyuan Zhao, Cen Chen, Songyou Peng, Min Wu, Zhongyao Cheng, Singee Teo, Le Zhang, Zeng Zeng

In this study, we applied powerful deep neural network and explored a process in the forecast of skeletal bone age with the specifically combine joints images to increase the performance accuracy compared with the whole hand images.

MiniMax Entropy Network: Learning Category-Invariant Features for Domain Adaptation

no code implementations21 Apr 2019 Chaofan Tao, Fengmao Lv, Lixin Duan, Min Wu

Unlike most existing approaches which employ a generator to deal with domain difference, MMEN focuses on learning the categorical information from unlabeled target samples with the help of labeled source samples.

Domain Adaptation

SL$^2$MF: Predicting Synthetic Lethality in Human Cancers via Logistic Matrix Factorization

no code implementations20 Oct 2018 Yong Liu, Min Wu, Chenghao Liu, Xiao-Li Li, Jie Zheng

Moreover, we also incorporate biological knowledge about genes from protein-protein interaction (PPI) data and Gene Ontology (GO).

A Game-Based Approximate Verification of Deep Neural Networks with Provable Guarantees

1 code implementation10 Jul 2018 Min Wu, Matthew Wicker, Wenjie Ruan, Xiaowei Huang, Marta Kwiatkowska

In this paper, we study two variants of pointwise robustness, the maximum safe radius problem, which for a given input sample computes the minimum distance to an adversarial example, and the feature robustness problem, which aims to quantify the robustness of individual features to adversarial perturbations.

Adversarial Attack Adversarial Defense +2

Concolic Testing for Deep Neural Networks

2 code implementations30 Apr 2018 Youcheng Sun, Min Wu, Wenjie Ruan, Xiaowei Huang, Marta Kwiatkowska, Daniel Kroening

Concolic testing combines program execution and symbolic analysis to explore the execution paths of a software program.

Global Robustness Evaluation of Deep Neural Networks with Provable Guarantees for the $L_0$ Norm

2 code implementations16 Apr 2018 Wenjie Ruan, Min Wu, Youcheng Sun, Xiaowei Huang, Daniel Kroening, Marta Kwiatkowska

In this paper we focus on the $L_0$ norm and aim to compute, for a trained DNN and an input, the maximal radius of a safe norm ball around the input within which there are no adversarial examples.

Adaptive Cost-sensitive Online Classification

no code implementations6 Apr 2018 Peilin Zhao, Yifan Zhang, Min Wu, Steven C. H. Hoi, Mingkui Tan, Junzhou Huang

Cost-Sensitive Online Classification has drawn extensive attention in recent years, where the main approach is to directly online optimize two well-known cost-sensitive metrics: (i) weighted sum of sensitivity and specificity; (ii) weighted misclassification cost.

Anomaly Detection Classification +2

Safety Verification of Deep Neural Networks

2 code implementations21 Oct 2016 Xiaowei Huang, Marta Kwiatkowska, Sen Wang, Min Wu

Our method works directly with the network code and, in contrast to existing methods, can guarantee that adversarial examples, if they exist, are found for the given region and family of manipulations.

Adversarial Attack Adversarial Defense +3

Efficient Estimation of Compressible State-Space Models with Application to Calcium Signal Deconvolution

no code implementations20 Oct 2016 Abbas Kazemipour, Ji Liu, Patrick Kanold, Min Wu, Behtash Babadi

In this paper, we consider linear state-space models with compressible innovations and convergent transition matrices in order to model spatiotemporally sparse transient events.

Sampling Requirements for Stable Autoregressive Estimation

no code implementations4 May 2016 Abbas Kazemipour, Sina Miran, Piya Pal, Behtash Babadi, Min Wu

Assuming that the parameters are compressible, we analyze the performance of the $\ell_1$-regularized least squares as well as a greedy estimator of the parameters and characterize the sampling trade-offs required for stable recovery in the non-asymptotic regime.

Model Selection

Robust Estimation of Self-Exciting Generalized Linear Models with Application to Neuronal Modeling

1 code implementation14 Jul 2015 Abbas Kazemipour, Min Wu, Behtash Babadi

We consider the problem of estimating self-exciting generalized linear models from limited binary observations, where the history of the process serves as the covariate.

Multi-label ensemble based on variable pairwise constraint projection

no code implementations8 Mar 2014 Ping Li, Hong Li, Min Wu

For the boosting-like strategy, we employ both the variable pairwise constraints and the bootstrap steps to diversify the base classifiers.

Classification General Classification +1

Sparse Norm Filtering

no code implementations17 May 2013 Chengxi Ye, DaCheng Tao, Mingli Song, David W. Jacobs, Min Wu

Optimization-based filtering smoothes an image by minimizing a fidelity function and simultaneously preserves edges by exploiting a sparse norm penalty over gradients.

Colorization Deblurring +2

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