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02/05/2023
On Kronecker Separability of Multiway Covariance
Multiway data analysis is aimed at inferring patterns from data represen...
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02/25/2022
An Improvement on the Hotelling T^2 Test Using the Ledoit-Wolf Nonlinear Shrinkage Estimator
Hotelling's T^2 test is a classical approach for discriminating the mean...
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12/09/2021
Fair Structure Learning in Heterogeneous Graphical Models
Inference of community structure in probabilistic graphical models may n...
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08/27/2021
Multimodal Data Fusion in High-Dimensional Heterogeneous Datasets via Generative Models
The commonly used latent space embedding techniques, such as Principal C...
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01/12/2021
A unified framework for correlation mining in ultra-high dimension
An important problem in large scale inference is the identification of v...
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09/10/2020
OrthoReg: Robust Network Pruning Using Orthonormality Regularization
Network pruning in Convolutional Neural Networks (CNNs) has been extensi...
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05/02/2020
Pattern-Based Analysis of Time Series: Estimation
While Internet of Things (IoT) devices and sensors create continuous str...
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10/02/2019
Geometric Online Adaptation: Graph-Based OSFS for Streaming Samples
Feature selection seeks a curated subset of available features such that...
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05/31/2019
Testing that a Local Optimum of the Likelihood is Globally Optimum using Reparameterized Embeddings
Many mathematical imaging problems are posed as non-convex optimization ...
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05/21/2019
Geometric Estimation of Multivariate Dependency
This paper proposes a geometric estimator of dependency between a pair o...
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04/07/2019
An unsupervised transfer learning algorithm for sleep monitoring
Objective: To develop multisensor-wearable-device sleep monitoring algor...
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02/10/2019
Feature Selection for multi-labeled variables via Dependency Maximization
Feature selection and reducing the dimensionality of data is an essentia...
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11/15/2018
Learning to Bound the Multi-class Bayes Error
In the context of supervised learning, meta learning uses features, meta...
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10/01/2018
Convergence Rates for Empirical Estimation of Binary Classification Bounds
Bounding the best achievable error probability for binary classification...
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10/01/2018
Part-Level Convolutional Neural Networks for Pedestrian Detection Using Saliency and Boundary Box Alignment
Pedestrians in videos have a wide range of appearances such as body pose...
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09/04/2018
Parity Crowdsourcing for Cooperative Labeling
Consider a database of k objects, e.g., a set of videos, where each obje...
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03/07/2018
Sequential Maximum Margin Classifiers for Partially Labeled Data
In many real-world applications, data is not collected as one batch, but...
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02/13/2018
A Dimension-Independent discriminant between distributions
Henze-Penrose divergence is a non-parametric divergence measure that can...
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12/18/2017
Model Reduction in Chemical Reaction Networks: A Data-Driven Sparse-Learning Approach
The reduction of large kinetic mechanisms is a crucial step for fluid dy...
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12/12/2017
A Data-Driven Sparse-Learning Approach to Model Reduction in Chemical Reaction Networks
In this paper, we propose an optimization-based sparse learning approach...
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12/01/2017
Fundamental Limits on Data Acquisition: Trade-offs between Sample Complexity and Query Difficulty
In this paper, we consider query-based data acquisition and the correspo...
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11/09/2017
Fast Meta-Learning for Adaptive Hierarchical Classifier Design
We propose a new splitting criterion for a meta-learning approach to mul...
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10/21/2017
Zeroth-Order Online Alternating Direction Method of Multipliers: Convergence Analysis and Applications
In this paper, we design and analyze a new zeroth-order online algorithm...
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08/08/2017
Multilayer Spectral Graph Clustering via Convex Layer Aggregation: Theory and Algorithms
Multilayer graphs are commonly used for representing different relations...
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04/18/2017
Accelerated Distributed Dual Averaging over Evolving Networks of Growing Connectivity
We consider the problem of accelerating distributed optimization in mult...
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02/21/2017
Direct estimation of density functionals using a polynomial basis
A number of fundamental quantities in statistical signal processing and ...
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02/16/2017
Latent Laplacian Maximum Entropy Discrimination for Detection of High-Utility Anomalies
Data-driven anomaly detection methods suffer from the drawback of detect...
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10/21/2016
Robust training on approximated minimal-entropy set
In this paper, we propose a general framework to learn a robust large-ma...
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04/11/2016
Phase Transitions and a Model Order Selection Criterion for Spectral Graph Clustering
One of the longstanding open problems in spectral graph clustering (SGC)...
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12/23/2015
Multi-centrality Graph Spectral Decompositions and their Application to Cyber Intrusion Detection
Many modern datasets can be represented as graphs and hence spectral dec...
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12/23/2015
Incremental Method for Spectral Clustering of Increasing Orders
The smallest eigenvalues and the associated eigenvectors (i.e., eigenpai...
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05/11/2015
Foundational principles for large scale inference: Illustrations through correlation mining
When can reliable inference be drawn in the "Big Data" context? This pap...
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02/26/2015
A Dictionary Approach to EBSD Indexing
We propose a framework for indexing of grain and sub-grain structures in...
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12/19/2014
Empirically Estimable Classification Bounds Based on a New Divergence Measure
Information divergence functions play a critical role in statistics and ...
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08/06/2014
Empirical non-parametric estimation of the Fisher Information
The Fisher information matrix (FIM) is a foundational concept in statist...
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04/06/2013
Nonlinear unmixing of hyperspectral images: models and algorithms
When considering the problem of unmixing hyperspectral images, most of t...
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03/15/2013
Variational Semi-blind Sparse Deconvolution with Orthogonal Kernel Bases and its Application to MRFM
We present a variational Bayesian method of joint image reconstruction a...
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03/21/2012
Semi-blind Sparse Image Reconstruction with Application to MRFM
We propose a solution to the image deconvolution problem where the convo...
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02/06/2011
Large Scale Correlation Screening
This paper treats the problem of screening for variables with high corre...
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12/22/2010
Regularized Least-Mean-Square Algorithms
We consider adaptive system identification problems with convex constrai...
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09/24/2009
Initialization Free Graph Based Clustering
This paper proposes an original approach to cluster multi-component data...
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02/14/2008