Search Results for author: Alfred Hero

Found 34 papers, 10 papers with code

Challenging Forgets: Unveiling the Worst-Case Forget Sets in Machine Unlearning

1 code implementation12 Mar 2024 Chongyu Fan, Jiancheng Liu, Alfred Hero, Sijia Liu

This leads to the problem of machine unlearning (MU), aiming to eliminate the influence of chosen data points on model performance, while still maintaining the model's utility post-unlearning.

Machine Unlearning

Gradient Coding through Iterative Block Leverage Score Sampling

no code implementations6 Aug 2023 Neophytos Charalambides, Mert Pilanci, Alfred Hero

This is then used to derive an approximate coded computing approach for first-order methods; known as gradient coding, to accelerate linear regression in the presence of failures in distributed computational networks, \textit{i. e.} stragglers.


Robustness-preserving Lifelong Learning via Dataset Condensation

no code implementations7 Mar 2023 Jinghan Jia, Yihua Zhang, Dogyoon Song, Sijia Liu, Alfred Hero

Most work in this learning paradigm has focused on resolving the problem of 'catastrophic forgetting,' which refers to a notorious dilemma between improving model accuracy over new data and retaining accuracy over previous data.

Adversarial Robustness Dataset Condensation +1

Incorporating Polar Field Data for Improved Solar Flare Prediction

no code implementations4 Dec 2022 Mehmet Aktukmak, Zeyu Sun, Monica Bobra, Tamas Gombosi, Ward B. Manchester, Yang Chen, Alfred Hero

In this paper, we consider incorporating data associated with the sun's north and south polar field strengths to improve solar flare prediction performance using machine learning models.

Solar Flare Prediction

A Graphical Model for Fusing Diverse Microbiome Data

1 code implementation21 Aug 2022 Mehmet Aktukmak, Haonan Zhu, Marc G. Chevrette, Julia Nepper, Shruthi Magesh, Jo Handelsman, Alfred Hero

We present a computationally scalable variational Expectation-Maximization (EM) algorithm for inferring the latent variables and the parameters of the model.

Dimensionality Reduction

Resolution Limits of Non-Adaptive 20 Questions Search for a Moving Target

no code implementations14 Jun 2022 Lin Zhou, Alfred Hero

Our task is to query the oracle as few times as possible to accurately estimate the location of the target at any specified time.

Predicting Solar Flares Using CNN and LSTM on Two Solar Cycles of Active Region Data

1 code implementation7 Apr 2022 Zeyu Sun, Monica G. Bobra, Xiantong Wang, Yu Wang, Hu Sun, Tamas Gombosi, Yang Chen, Alfred Hero

We consider the flare prediction problem that distinguishes flare-imminent active regions that produce an M- or X-class flare in the future 24 hours, from quiet active regions that do not produce any flare within $\pm 24$ hours.


Multiway Ensemble Kalman Filter

1 code implementation8 Dec 2021 Yu Wang, Alfred Hero

In this work, we study the emergence of sparsity and multiway structures in second-order statistical characterizations of dynamical processes governed by partial differential equations (PDEs).

Multi-Trigger-Key: Towards Multi-Task Privacy Preserving In Deep Learning

no code implementations6 Oct 2021 Ren Wang, Zhe Xu, Alfred Hero

Deep learning-based Multi-Task Classification (MTC) is widely used in applications like facial attributes and healthcare that warrant strong privacy guarantees.

Privacy Preserving

Multi-Trigger-Key: Towards Multi-Task Privacy-Preserving In Deep Learning

no code implementations29 Sep 2021 Ren Wang, Zhe Xu, Alfred Hero

Deep learning-based Multi-Task Classification (MTC) is widely used in applications like facial attribute and healthcare that warrant strong privacy guarantees.

Attribute Privacy Preserving

Deep Adversarially-Enhanced k-Nearest Neighbors

no code implementations15 Aug 2021 Ren Wang, Tianqi Chen, Alfred Hero

Recent works have theoretically and empirically shown that deep neural networks (DNNs) have an inherent vulnerability to small perturbations.

ASK: Adversarial Soft k-Nearest Neighbor Attack and Defense

1 code implementation27 Jun 2021 Ren Wang, Tianqi Chen, Philip Yao, Sijia Liu, Indika Rajapakse, Alfred Hero

K-Nearest Neighbor (kNN)-based deep learning methods have been applied to many applications due to their simplicity and geometric interpretability.

RAILS: A Robust Adversarial Immune-inspired Learning System

1 code implementation27 Jun 2021 Ren Wang, Tianqi Chen, Stephen Lindsly, Cooper Stansbury, Alnawaz Rehemtulla, Indika Rajapakse, Alfred Hero

Initializing a population of exemplars that is balanced across classes, RAILS starts from a uniform label distribution that encourages diversity and uses an evolutionary optimization process to adaptively adjust the predictive label distribution in a manner that emulates the way the natural immune system recognizes novel pathogens.

Adversarial Defense Adversarial Robustness +2

Immuno-mimetic Deep Neural Networks (Immuno-Net)

no code implementations27 Jun 2021 Ren Wang, Tianqi Chen, Stephen Lindsly, Cooper Stansbury, Indika Rajapakse, Alfred Hero

This immuno-mimetic model leads to a new computational biology framework for robustification of deep neural networks against adversarial attacks.

Image Classification

SG-PALM: a Fast Physically Interpretable Tensor Graphical Model

1 code implementation26 May 2021 Yu Wang, Alfred Hero

We propose a new graphical model inference procedure, called SG-PALM, for learning conditional dependency structure of high-dimensional tensor-variate data.

Spatio-Temporal Forecasting

RAILS: A Robust Adversarial Immune-inspired Learning System

no code implementations18 Dec 2020 Ren Wang, Tianqi Chen, Stephen Lindsly, Alnawaz Rehemtulla, Alfred Hero, Indika Rajapakse

RAILS incorporates an Adaptive Immune System Emulation (AISE), which emulates in silico the biological mechanisms that are used to defend the host against attacks by pathogens.

Adversarial Defense Image Classification

A Primer on Zeroth-Order Optimization in Signal Processing and Machine Learning

no code implementations11 Jun 2020 Sijia Liu, Pin-Yu Chen, Bhavya Kailkhura, Gaoyuan Zhang, Alfred Hero, Pramod K. Varshney

Zeroth-order (ZO) optimization is a subset of gradient-free optimization that emerges in many signal processing and machine learning applications.

BIG-bench Machine Learning Management

The Sylvester Graphical Lasso (SyGlasso)

1 code implementation1 Feb 2020 Yu Wang, Byoungwook Jang, Alfred Hero

We apply the SyGlasso to an electroencephalography (EEG) study to compare the brain connectivity of alcoholic and nonalcoholic subjects.


Solar Flare Intensity Prediction with Machine Learning Models

1 code implementation12 Dec 2019 Zhenbang Jiao, Hu Sun, Xiantong Wang, Ward Manchester, Tamas Gombosi, Alfred Hero, Yang Chen

We develop a mixed Long Short Term Memory (LSTM) regression model to predict the maximum solar flare intensity within a 24-hour time window 0$\sim$24, 6$\sim$30, 12$\sim$36 and 24$\sim$48 hours ahead of time using 6, 12, 24 and 48 hours of data (predictors) for each Helioseismic and Magnetic Imager (HMI) Active Region Patch (HARP).

Solar and Stellar Astrophysics

Learning to Benchmark: Determining Best Achievable Misclassification Error from Training Data

2 code implementations16 Sep 2019 Morteza Noshad, Li Xu, Alfred Hero

In this problem the objective is to establish statistically consistent estimates of the Bayes misclassification error rate without having to learn a Bayes-optimal classifier.

Time-Varying Interaction Estimation Using Ensemble Methods

no code implementations25 Jun 2019 Brandon Oselio, Amir Sadeghian, Silvio Savarese, Alfred Hero

Directed information (DI) is a useful tool to explore time-directed interactions in multivariate data.

Ensemble Learning

Minimum Volume Topic Modeling

no code implementations3 Apr 2019 Byoungwook Jang, Alfred Hero

We propose a new topic modeling procedure that takes advantage of the fact that the Latent Dirichlet Allocation (LDA) log likelihood function is asymptotically equivalent to the logarithm of the volume of the topic simplex.

Model Optimization

Latent heterogeneous multilayer community detection

no code implementations16 Jun 2018 Hafiz Tiomoko Ali, Sijia Liu, Yasin Yilmaz, Romain Couillet, Indika Rajapakse, Alfred Hero

We propose a method for simultaneously detecting shared and unshared communities in heterogeneous multilayer weighted and undirected networks.

Community Detection

Robust SAR STAP via Kronecker Decomposition

no code implementations5 May 2016 Kristjan Greenewald, Edmund Zelnio, Alfred Hero

This paper proposes a spatio-temporal decomposition for the detection of moving targets in multiantenna SAR.

Nonstationary Distance Metric Learning

no code implementations11 Mar 2016 Kristjan Greenewald, Stephen Kelley, Alfred Hero

Recent work in distance metric learning has focused on learning transformations of data that best align with provided sets of pairwise similarity and dissimilarity constraints.

Clustering Metric Learning +1

Multimodal MRI Neuroimaging with Motion Compensation Based on Particle Filtering

no code implementations11 Nov 2015 Yu-Hui Chen, Roni Mittelman, Boklye Kim, Charles Meyer, Alfred Hero

Head motion in fMRI acquired using slice-based Echo Planar Imaging (EPI) can be estimated and compensated by aligning the images onto a reference volume through image registration.

Image Registration Motion Compensation +1

Statistical Estimation and Clustering of Group-invariant Orientation Parameters

no code implementations15 Mar 2015 Yu-Hui Chen, Dennis Wei, Gregory Newstadt, Marc DeGraef, Jeffrey Simmons, Alfred Hero

We treat the problem of estimation of orientation parameters whose values are invariant to transformations from a spherical symmetry group.


Coercive Region-level Registration for Multi-modal Images

no code implementations26 Feb 2015 Yu-Hui Chen, Dennis Wei, Gregory Newstadt, Jeffrey Simmons, Alfred Hero

We propose a coercive approach to simultaneously register and segment multi-modal images which share similar spatial structure.

Two-stage Sampling, Prediction and Adaptive Regression via Correlation Screening (SPARCS)

no code implementations22 Feb 2015 Hamed Firouzi, Alfred Hero, Bala Rajaratnam

In the first stage we collect a few ($n$) expensive samples $\{y_i,\mathbf x_i\}_{i=1}^n$, at the full dimension $p\gg n$ of $\mathbf X$, winnowing the number of variables down to a smaller dimension $l < p$ using a type of cross-correlation or regression coefficient screening.

regression Vocal Bursts Valence Prediction

Multivariate f-divergence Estimation With Confidence

no code implementations NeurIPS 2014 Kevin Moon, Alfred Hero

The problem of f-divergence estimation is important in the fields of machine learning, information theory, and statistics.

General Classification

Parameter estimation in spherical symmetry groups

no code implementations10 Nov 2014 Yu-Hui Chen, Dennis Wei, Gregory Newstadt, Marc DeGraef, Jeffrey Simmons, Alfred Hero

This paper considers statistical estimation problems where the probability distribution of the observed random variable is invariant with respect to actions of a finite topological group.

Predictive Correlation Screening: Application to Two-stage Predictor Design in High Dimension

no code implementations10 Mar 2013 Hamed Firouzi, Bala Rajaratnam, Alfred Hero

We introduce a new approach to variable selection, called Predictive Correlation Screening, for predictor design.

Variable Selection

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