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07/18/2023
Accuracy versus time frontiers of semi-supervised and self-supervised learning on medical images
For many applications of classifiers to medical images, a trustworthy la...
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04/02/2023
A principled approach to model validation in domain generalization
Domain generalization aims to learn a model with good generalization abi...
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02/15/2023
On Rank Energy Statistics via Optimal Transport: Continuity, Convergence, and Change Point Detection
This paper considers the use of recently proposed optimal transport-base...
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11/14/2022
Alternating minimization algorithm with initialization analysis for r-local and k-sparse unlabeled sensing
The unlabeled sensing problem is to recover an unknown signal from permu...
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10/26/2022
Trade-off between reconstruction loss and feature alignment for domain generalization
Domain generalization (DG) is a branch of transfer learning that aims to...
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10/21/2022
Geometric Sparse Coding in Wasserstein Space
Wasserstein dictionary learning is an unsupervised approach to learning ...
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10/04/2022
Non-Parametric and Regularized Dynamical Wasserstein Barycenters for Time-Series Analysis
We consider probabilistic time-series models for systems that gradually ...
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08/31/2022
Supervised Contrastive Learning with Hard Negative Samples
Unsupervised contrastive learning (UCL) is a self-supervised learning te...
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08/01/2022
Joint covariate-alignment and concept-alignment: a framework for domain generalization
In this paper, we propose a novel domain generalization (DG) framework b...
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05/31/2022
Easy Variational Inference for Categorical Models via an Independent Binary Approximation
We pursue tractable Bayesian analysis of generalized linear models (GLMs...
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01/28/2022
Measure Estimation in the Barycentric Coding Model
This paper considers the problem of measure estimation under the barycen...
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01/25/2022
Conditional entropy minimization principle for learning domain invariant representation features
Invariance principle-based methods, for example, Invariant Risk Minimiza...
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11/04/2021
Hard Negative Sampling via Regularized Optimal Transport for Contrastive Representation Learning
We study the problem of designing hard negative sampling distributions f...
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11/01/2021
Interpretable contrastive word mover's embedding
This paper shows that a popular approach to the supervised embedding of ...
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10/29/2021
Robust and efficient change point detection using novel multivariate rank-energy GoF test
In this paper, we use and further develop upon a recently proposed multi...
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10/29/2021
Learning generative models for valid knockoffs using novel multivariate-rank based statistics
We consider the problem of generating valid knockoffs for knockoff filte...
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10/26/2021
r-local sensing: Improved algorithm and applications
The unlabeled sensing problem is to solve a noisy linear system of equat...
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10/13/2021
Dynamical Wasserstein Barycenters for Time-series Modeling
Many time series can be modeled as a sequence of segments representing h...
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09/04/2021
Barycenteric distribution alignment and manifold-restricted invertibility for domain generalization
For the Domain Generalization (DG) problem where the hypotheses are comp...
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03/16/2021
Soft and subspace robust multivariate rank tests based on entropy regularized optimal transport
In this paper, we extend the recently proposed multivariate rank energy ...
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03/12/2021
Multiview Sensing With Unknown Permutations: An Optimal Transport Approach
In several applications, including imaging of deformable objects while i...
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11/26/2020
Automatic coding of students' writing via Contrastive Representation Learning in the Wasserstein space
Qualitative analysis of verbal data is of central importance in the lear...
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07/22/2020
Robust Machine Learning via Privacy/Rate-Distortion Theory
Robust machine learning formulations have emerged to address the prevale...
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07/11/2020
Representation Learning via Adversarially-Contrastive Optimal Transport
In this paper, we study the problem of learning compact (low-dimensional...
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06/09/2020
On Matched Filtering for Statistical Change Point Detection
Non-parametric and distribution-free two-sample tests have been the foun...
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11/04/2019
Optimal Transport Based Change Point Detection and Time Series Segment Clustering
Two common problems in time series analysis are the decomposition of the...
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08/02/2019
On the modes of convergence of Stochastic Optimistic Mirror Descent (OMD) for saddle point problems
In this article, we study the convergence of Mirror Descent (MD) and Opt...
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08/20/2018
Multi-View Graph Embedding Using Randomized Shortest Paths
Real-world data sets often provide multiple types of information about t...
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03/13/2018
Principal Component Analysis with Tensor Train Subspace
Tensor train is a hierarchical tensor network structure that helps allev...
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12/03/2017
Tensor Train Neighborhood Preserving Embedding
In this paper, we propose a Tensor Train Neighborhood Preserving Embeddi...
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08/26/2017
Faster Clustering via Non-Backtracking Random Walks
This paper presents VEC-NBT, a variation on the unsupervised graph clust...
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06/18/2017
Sample, computation vs storage tradeoffs for classification using tensor subspace models
In this paper, we exhibit the tradeoffs between the (training) sample, c...
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04/10/2017
Word Embeddings via Tensor Factorization
Most popular word embedding techniques involve implicit or explicit fact...
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10/15/2016
Unsupervised clustering under the Union of Polyhedral Cones (UOPC) model
In this paper, we consider clustering data that is assumed to come from ...
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07/11/2016
On Deterministic Conditions for Subspace Clustering under Missing Data
In this paper we present deterministic conditions for success of sparse ...
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12/31/2015
Denoising and Completion of 3D Data via Multidimensional Dictionary Learning
In this paper a new dictionary learning algorithm for multidimensional d...
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12/21/2015
Multilinear Subspace Clustering
In this paper we present a new model and an algorithm for unsupervised c...
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10/15/2015
Group-Invariant Subspace Clustering
In this paper we consider the problem of group invariant subspace cluste...
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08/14/2015
Information-theoretic Bounds on Matrix Completion under Union of Subspaces Model
In this short note we extend some of the recent results on matrix comple...
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08/10/2015
Adaptive Sampling of RF Fingerprints for Fine-grained Indoor Localization
Indoor localization is a supporting technology for a broadening range of...
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02/16/2015
Exact tensor completion using t-SVD
In this paper we focus on the problem of completion of multidimensional ...
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12/22/2014
Clustering multi-way data: a novel algebraic approach
In this paper, we develop a method for unsupervised clustering of two-wa...
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07/07/2014
Novel methods for multilinear data completion and de-noising based on tensor-SVD
In this paper we propose novel methods for completion (from limited samp...
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03/24/2014
First Order Methods for Robust Non-negative Matrix Factorization for Large Scale Noisy Data
Nonnegative matrix factorization (NMF) has been shown to be identifiable...
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01/08/2014
Robust Large Scale Non-negative Matrix Factorization using Proximal Point Algorithm
A robust algorithm for non-negative matrix factorization (NMF) is presen...
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07/02/2013