research
∙
08/06/2023
Gradient Coding through Iterative Block Leverage Score Sampling
We generalize the leverage score sampling sketch for â„“_2-subspace embedd...
share
research
∙
05/18/2023
Minimum-Risk Recalibration of Classifiers
Recalibrating probabilistic classifiers is vital for enhancing the relia...
research
∙
03/07/2023
Robustness-preserving Lifelong Learning via Dataset Condensation
Lifelong learning (LL) aims to improve a predictive model as the data so...
research
∙
01/09/2023
Federated Coded Matrix Inversion
Federated learning (FL) is a decentralized model for training data distr...
research
∙
12/04/2022
Incorporating Polar Field Data for Improved Solar Flare Prediction
In this paper, we consider incorporating data associated with the sun's ...
research
∙
12/04/2022
Kronecker-structured Covariance Models for Multiway Data
Many applications produce multiway data of exceedingly high dimension. M...
research
∙
08/21/2022
A Graphical Model for Fusing Diverse Microbiome Data
This paper develops a Bayesian graphical model for fusing disparate type...
research
∙
07/13/2022
Secure Linear MDS Coded Matrix Inversion
A cumbersome operation in many scientific fields, is inverting large ful...
research
∙
06/14/2022
Resolution Limits of Non-Adaptive 20 Questions Search for a Moving Target
Using the 20 questions estimation framework with query-dependent noise, ...
research
∙
04/07/2022
Predicting Solar Flares Using CNN and LSTM on Two Solar Cycles of Active Region Data
We consider the flare prediction problem that distinguishes flare-immine...
research
∙
01/23/2022
Asymptotics for Outlier Hypothesis Testing
We revisit the outlier hypothesis testing framework of Li et al. (TIT 20...
research
∙
12/08/2021
Multiway Ensemble Kalman Filter
In this work, we study the emergence of sparsity and multiway structures...
research
∙
10/06/2021
Multi-Trigger-Key: Towards Multi-Task Privacy Preserving In Deep Learning
Deep learning-based Multi-Task Classification (MTC) is widely used in ap...
research
∙
06/27/2021
ASK: Adversarial Soft k-Nearest Neighbor Attack and Defense
K-Nearest Neighbor (kNN)-based deep learning methods have been applied t...
research
∙
06/27/2021
Immuno-mimetic Deep Neural Networks (Immuno-Net)
Biomimetics has played a key role in the evolution of artificial neural ...
research
∙
05/26/2021
SG-PALM: a Fast Physically Interpretable Tensor Graphical Model
We propose a new graphical model inference procedure, called SG-PALM, fo...
research
∙
05/01/2021
Achievable Resolution Limits for the Noisy Adaptive 20 Questions Problem
We study the achievable performance of adaptive query procedures for the...
research
∙
03/15/2021
Resolution Limits of 20 Questions Search Strategies for Moving Targets
We establish fundamental limits of tracking a moving target over the uni...
research
∙
01/18/2021
Resolution Limits of Non-Adaptive 20 Questions Search for Multiple Targets
We study the problem of simultaneous search for multiple targets over a ...
research
∙
12/18/2020
RAILS: A Robust Adversarial Immune-inspired Learning System
Adversarial attacks against deep neural networks are continuously evolvi...
research
∙
11/19/2020
Approximate Weighted CR Coded Matrix Multiplication
One of the most common, but at the same time expensive operations in lin...
research
∙
09/08/2020
Second-Order Asymptotically Optimal Universal Outlying Sequence Detection with Reject Option
Motivated by practical machine learning applications, we revisit the out...
research
∙
04/15/2020
Resolution Limits of Non-Adaptive Querying for Noisy 20 Questions Estimation
We study fundamental limits of estimation accuracy for the noisy 20 ques...
research
∙
02/01/2020
The Sylvester Graphical Lasso (SyGlasso)
This paper introduces the Sylvester graphical lasso (SyGlasso) that capt...
research
∙
09/27/2019
Resolution Limits of Noisy 20 Questions Estimation
We establish fundamental limits on estimation accuracy for the noisy 20 ...
research
∙
09/16/2019
Learning to Benchmark: Determining Best Achievable Misclassification Error from Training Data
We address the problem of learning to benchmark the best achievable clas...
research
∙
09/09/2019
A Hierarchical Bayesian Approach to Neutron Spectrum Unfolding with Organic Scintillators
We propose a hierarchical Bayesian model and state-of-art Monte Carlo sa...
research
∙
06/25/2019
Time-Varying Interaction Estimation Using Ensemble Methods
Directed information (DI) is a useful tool to explore time-directed inte...
research
∙
05/03/2019
Enterprise Cyber Resiliency Against Lateral Movement: A Graph Theoretic Approach
Lateral movement attacks are a serious threat to enterprise security. In...
research
∙
04/03/2019
Minimum Volume Topic Modeling
We propose a new topic modeling procedure that takes advantage of the fa...
research
∙
01/28/2019
Hierarchical network models for structured exchangeable interaction processes
Network data often arises via a series of structured interactions among ...
research
∙
01/05/2019
Exponential Strong Converse for Successive Refinement with Causal Decoder Side Information
We revisit the successive refinement problem with causal decoder side in...
research
∙
06/16/2018
Latent heterogeneous multilayer community detection
We propose a method for simultaneously detecting shared and unshared com...
research
∙
04/24/2018
Anomaly Detection in Partially Observed Traffic Networks
This paper addresses the problem of detecting anomalous activity in traf...
research
∙
03/11/2016
Nonstationary Distance Metric Learning
Recent work in distance metric learning has focused on learning transfor...
research
∙
11/11/2015
Multimodal MRI Neuroimaging with Motion Compensation Based on Particle Filtering
Head movement during scanning impedes activation detection in fMRI studi...
research
∙
03/15/2015
Statistical Estimation and Clustering of Group-invariant Orientation Parameters
We treat the problem of estimation of orientation parameters whose value...
research
∙
02/26/2015
Coercive Region-level Registration for Multi-modal Images
We propose a coercive approach to simultaneously register and segment mu...
research
∙
02/22/2015
Two-stage Sampling, Prediction and Adaptive Regression via Correlation Screening (SPARCS)
This paper proposes a general adaptive procedure for budget-limited pred...
research
∙
11/10/2014
Parameter estimation in spherical symmetry groups
This paper considers statistical estimation problems where the probabili...
research
∙
01/14/2014
Detection of Anomalous Crowd Behavior Using Spatio-Temporal Multiresolution Model and Kronecker Sum Decompositions
In this work we consider the problem of detecting anomalous spatio-tempo...
research
∙
03/10/2013
Predictive Correlation Screening: Application to Two-stage Predictor Design in High Dimension
We introduce a new approach to variable selection, called Predictive Cor...
research
∙
07/16/2003
