Alfred O. Hero III

research

∙ 08/08/2023

Iterative Sketching for Secure Coded Regression

In this work, we propose methods for speeding up linear regression distr...

0 Neophytos Charalambides, et al. ∙

research

∙ 04/17/2023

Graph Sparsification by Approximate Matrix Multiplication

Graphs arising in statistical problems, signal processing, large network...

0 Neophytos Charalambides, et al. ∙

research

∙ 08/16/2022

SOLBP: Second-Order Loopy Belief Propagation for Inference in Uncertain Bayesian Networks

In second-order uncertain Bayesian networks, the conditional probabiliti...

0 Conrad D. Hougen, et al. ∙

research

∙ 08/08/2022

Uncertain Bayesian Networks: Learning from Incomplete Data

When the historical data are limited, the conditional probabilities asso...

0 Conrad D. Hougen, et al. ∙

research

∙ 07/22/2022

High dimensional stochastic linear contextual bandit with missing covariates

Recent works in bandit problems adopted lasso convergence theory in the ...

0 Byoungwook Jang, et al. ∙

research

∙ 01/21/2022

Orthonormal Sketches for Secure Coded Regression

In this work, we propose a method for speeding up linear regression dist...

0 Neophytos Charalambides, et al. ∙

research

∙ 09/22/2021

Numerically Stable Binary Coded Computations

This paper addresses the gradient coding and coded matrix multiplication...

0 Neophytos Charalambides, et al. ∙

research

∙ 03/15/2021

Data Discovery Using Lossless Compression-Based Sparse Representation

Sparse representation has been widely used in data compression, signal a...

0 Elyas Sabeti, et al. ∙

research

∙ 03/05/2020

Straggler Robust Distributed Matrix Inverse Approximation

A cumbersome operation in numerical analysis and linear algebra, optimiz...

0 Neophytos Charalambides, et al. ∙

research

∙ 02/13/2020

The Power of Graph Convolutional Networks to Distinguish Random Graph Models: Short Version

Graph convolutional networks (GCNs) are a widely used method for graph r...

0 Abram Magner, et al. ∙

research

∙ 01/30/2020

Numerically Stable Binary Gradient Coding

A major hurdle in machine learning is scalability to massive datasets. O...

0 Neophytos Charalambides, et al. ∙

research

∙ 01/30/2020

Weighted Gradient Coding with Leverage Score Sampling

A major hurdle in machine learning is scalability to massive datasets. A...

0 Neophytos Charalambides, et al. ∙

research

∙ 10/28/2019

The Power of Graph Convolutional Networks to Distinguish Random Graph Models

Graph convolutional networks (GCNs) are a widely used method for graph r...

0 Abram Magner, et al. ∙

research

∙ 01/28/2019

Semi-supervised Learning in Network-Structured Data via Total Variation Minimization

We propose and analyze a method for semi-supervised learning from partia...

18 Alexander Jung, et al. ∙

research

∙ 01/27/2018

Scalable Mutual Information Estimation using Dependence Graphs

We propose a unified method for empirical non-parametric estimation of g...

0 Morteza Noshad, et al. ∙

research

∙ 01/01/2018

Scalable Hash-Based Estimation of Divergence Measures

We propose a scalable divergence estimation method based on hashing. Con...

0 Morteza Noshad, et al. ∙

research

∙ 11/15/2017

Semiblind subgraph reconstruction in Gaussian graphical models

Consider a social network where only a few nodes (agents) have meaningfu...

0 Tianpei Xie, et al. ∙

research

∙ 10/31/2017

Rate-optimal Meta Learning of Classification Error

Meta learning of optimal classifier error rates allows an experimenter t...

0 Morteza Noshad Iranzad, et al. ∙

research

∙ 02/17/2017

Direct Estimation of Information Divergence Using Nearest Neighbor Ratios

We propose a direct estimation method for Rényi and f-divergence measure...

0 Morteza Noshad, et al. ∙

research

∙ 01/07/2017

Similarity Function Tracking using Pairwise Comparisons

Recent work in distance metric learning has focused on learning transfor...

0 Kristjan Greenewald, et al. ∙

research

∙ 09/23/2016

Multilayer Spectral Graph Clustering via Convex Layer Aggregation

Multilayer graphs are commonly used for representing different relations...

0 Pin-Yu Chen, et al. ∙

research

∙ 09/21/2016

AMOS: An Automated Model Order Selection Algorithm for Spectral Graph Clustering

One of the longstanding problems in spectral graph clustering (SGC) is t...

0 Pin-Yu Chen, et al. ∙

research

∙ 09/13/2016

Information Theoretic Structure Learning with Confidence

Information theoretic measures (e.g. the Kullback Liebler divergence and...

0 Kevin R. Moon, et al. ∙

research

∙ 10/13/2015

The intrinsic value of HFO features as a biomarker of epileptic activity

High frequency oscillations (HFOs) are a promising biomarker of epilepti...

0 Stephen V. Gliske, et al. ∙

research

∙ 08/20/2015

Multi-criteria Similarity-based Anomaly Detection using Pareto Depth Analysis

We consider the problem of identifying patterns in a data set that exhib...

0 Ko-Jen Hsiao, et al. ∙

research

∙ 04/27/2015

Meta learning of bounds on the Bayes classifier error

Meta learning uses information from base learners (e.g. classifiers or e...

0 Kevin R. Moon, et al. ∙

research

∙ 04/10/2015

Image patch analysis of sunspots and active regions. II. Clustering via matrix factorization

Separating active regions that are quiet from potentially eruptive ones ...

0 Kevin R. Moon, et al. ∙

research

∙ 04/09/2015

Phase Transitions in Spectral Community Detection of Large Noisy Networks

In this paper, we study the sensitivity of the spectral clustering based...

0 Pin-Yu Chen, et al. ∙

research

∙ 03/13/2015

Image patch analysis of sunspots and active regions. I. Intrinsic dimension and correlation analysis

The flare-productivity of an active region is observed to be related to ...

0 Kevin R. Moon, et al. ∙

research

∙ 11/07/2014

Multivariate f-Divergence Estimation With Confidence

The problem of f-divergence estimation is important in the fields of mac...

0 Kevin R. Moon, et al. ∙

research

∙ 09/25/2014

MIST: L0 Sparse Linear Regression with Momentum

Significant attention has been given to minimizing a penalized least squ...

0 Goran Marjanovic, et al. ∙

research

∙ 08/05/2014

L0 Sparse Inverse Covariance Estimation

Recently, there has been focus on penalized log-likelihood covariance es...

0 Goran Marjanovic, et al. ∙

research

∙ 06/24/2014

Image patch analysis and clustering of sunspots: a dimensionality reduction approach

Sunspots, as seen in white light or continuum images, are associated wit...

0 Kevin R. Moon, et al. ∙

research

∙ 05/19/2014

Kronecker PCA Based Spatio-Temporal Modeling of Video for Dismount Classification

We consider the application of KronPCA spatio-temporal modeling techniqu...

0 Kristjan H. Greenewald, et al. ∙

research

∙ 02/21/2014

Pareto-depth for Multiple-query Image Retrieval

Most content-based image retrieval systems consider either one single qu...

0 Ko-Jen Hsiao, et al. ∙

research

∙ 07/27/2013

Kronecker Sum Decompositions of Space-Time Data

In this paper we consider the use of the space vs. time Kronecker produc...

0 Kristjan Greenewald, et al. ∙

research

∙ 04/30/2013

Revealing social networks of spammers through spectral clustering

To date, most studies on spam have focused only on the spamming phase of...

0 Kevin S. Xu, et al. ∙

research

∙ 03/19/2013

Marginal Likelihoods for Distributed Parameter Estimation of Gaussian Graphical Models

We consider distributed estimation of the inverse covariance matrix, als...

0 Zhaoshi Meng, et al. ∙

research

∙ 02/12/2013

Covariance Estimation in High Dimensions via Kronecker Product Expansions

This paper presents a new method for estimating high dimensional covaria...

0 Theodoros Tsiligkaridis, et al. ∙

research

∙ 02/03/2013

Correcting Camera Shake by Incremental Sparse Approximation

The problem of deblurring an image when the blur kernel is unknown remai...

0 Paul Shearer, et al. ∙

research

∙ 04/03/2012

Convergence Properties of Kronecker Graphical Lasso Algorithms

This paper studies iteration convergence of Kronecker graphical lasso (K...

0 Theodoros Tsiligkaridis, et al. ∙

research

∙ 10/17/2011

Multi-criteria Anomaly Detection using Pareto Depth Analysis

We consider the problem of identifying patterns in a data set that exhib...

0 Ko-Jen Hsiao, et al. ∙

research

∙ 05/09/2011

Order-preserving factor analysis (OPFA)

We present a novel factor analysis method that can be applied to the dis...

0 Arnau Tibau Puig, et al. ∙

research

∙ 04/11/2011

Adaptive Evolutionary Clustering

In many practical applications of clustering, the objects to be clustere...

0 Kevin S. Xu, et al. ∙

research

∙ 01/29/2011

Recursive ℓ_1,∞ Group lasso

We introduce a recursive adaptive group lasso algorithm for real-time pe...

0 Yilun Chen, et al. ∙

research

∙ 12/19/2010

Empirical estimation of entropy functionals with confidence

This paper introduces a class of k-nearest neighbor (k-NN) estimators ca...

0 Kumar Sricharan, et al. ∙

research

∙ 04/14/2010

Spatio-Temporal Graphical Model Selection

We consider the problem of estimating the topology of spatial interactio...

0 Patrick L. Harrington Jr., et al. ∙

research

∙ 09/29/2008

An Information Geometric Framework for Dimensionality Reduction

This report concerns the problem of dimensionality reduction through inf...

0 Kevin M. Carter, et al. ∙

research

∙ 08/18/2008

Decomposable Principal Component Analysis

We consider principal component analysis (PCA) in decomposable Gaussian ...

0 Ami Wiesel, et al. ∙

research

∙ 04/17/2008

Information Preserving Component Analysis: Data Projections for Flow Cytometry Analysis

Flow cytometry is often used to characterize the malignant cells in leuk...

0 Kevin M. Carter, et al. ∙

Alfred O. Hero III

Featured Co-authors