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05/06/2023
On High-dimensional and Low-rank Tensor Bandits
Most existing studies on linear bandits focus on the one-dimensional cha...
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10/16/2022
Finding the smallest or largest element of a tensor from its low-rank factors
We consider the problem of finding the smallest or largest entry of a te...
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10/13/2022
Learning Multivariate CDFs and Copulas using Tensor Factorization
Learning the multivariate distribution of data is a core challenge in st...
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12/31/2021
Uncovering migration systems through spatio-temporal tensor co-clustering
A central problem in the study of human mobility is that of migration sy...
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06/20/2021
Low-rank Characteristic Tensor Density Estimation Part II: Compression and Latent Density Estimation
Learning generative probabilistic models is a core problem in machine le...
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03/18/2021
Probabilistic Simplex Component Analysis
This study presents PRISM, a probabilistic simplex component analysis ap...
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02/05/2021
Exploring the Subgraph Density-Size Trade-off via the Lovász Extension
Given an undirected graph, the Densest-k-Subgraph problem (DkS) seeks to...
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12/20/2020
eTREE: Learning Tree-structured Embeddings
Matrix factorization (MF) plays an important role in a wide range of mac...
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12/08/2020
STELAR: Spatio-temporal Tensor Factorization with Latent Epidemiological Regularization
Accurate prediction of the transmission of epidemic diseases such as COV...
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11/03/2020
GAGE: Geometry Preserving Attributed Graph Embeddings
Node representation learning is the task of extracting concise and infor...
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10/30/2020
Information-theoretic Feature Selection via Tensor Decomposition and Submodularity
Feature selection by maximizing high-order mutual information between th...
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10/22/2020
TeX-Graph: Coupled tensor-matrix knowledge-graph embedding for COVID-19 drug repurposing
Knowledge graphs (KGs) are powerful tools that codify relational behavio...
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10/01/2020
PHASED: Phase-Aware Submodularity-Based Energy Disaggregation
Energy disaggregation is the task of discerning the energy consumption o...
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08/27/2020
Nonparametric Multivariate Density Estimation: A Low-Rank Characteristic Function Approach
Effective non-parametric density estimation is a key challenge in high-d...
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08/18/2020
Mining Large Quasi-cliques with Quality Guarantees from Vertex Neighborhoods
Mining dense subgraphs is an important primitive across a spectrum of gr...
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03/27/2020
GRATE: Granular Recovery of Aggregated Tensor Data by Example
In this paper, we address the challenge of recovering an accurate breakd...
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03/25/2020
Generalized Canonical Correlation Analysis: A Subspace Intersection Approach
Generalized Canonical Correlation Analysis (GCCA) is an important tool t...
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03/04/2020
Reliable Detection of Unknown Cell-Edge Users Via Canonical Correlation Analysis
Providing reliable service to users close to the edge between cells rema...
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10/26/2019
PREMA: Principled Tensor Data Recovery from Multiple Aggregated Views
Multidimensional data have become ubiquitous and are frequently involved...
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07/27/2019
REP: Predicting the Time-Course of Drug Sensitivity
The biological processes involved in a drug's mechanisms of action are o...
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06/13/2019
Nonlinear System Identification via Tensor Completion
Function approximation from input and output data pairs constitutes a fu...
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04/28/2019
Machine Learning in the Air
Thanks to the recent advances in processing speed and data acquisition a...
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04/02/2019
Learning Mixtures of Smooth Product Distributions: Identifiability and Algorithm
We study the problem of learning a mixture model of non-parametric produ...
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03/26/2019
Energy Storage Management via Deep Q-Networks
Energy storage devices represent environmentally friendly candidates to ...
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01/06/2019
Learning Nonlinear Mixtures: Identifiability and Algorithm
Linear mixture models have proven very useful in a plethora of applicati...
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10/29/2018
From Gene Expression to Drug Response: A Collaborative Filtering Approach
Predicting the response of cancer cells to drugs is an important problem...
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09/22/2018
Coupled Graphs and Tensor Factorization for Recommender Systems and Community Detection
Joint analysis of data from multiple information repositories facilitate...
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04/24/2018
Structured SUMCOR Multiview Canonical Correlation Analysis for Large-Scale Data
The sum-of-correlations (SUMCOR) formulation of generalized canonical co...
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03/03/2018
Nonnegative Matrix Factorization for Signal and Data Analytics: Identifiability, Algorithms, and Applications
Nonnegative matrix factorization (NMF) has become a workhorse for signal...
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03/02/2018
Mirror-Prox SCA Algorithm for Multicast Beamforming and Antenna Selection
This paper considers the (NP-)hard problem of joint multicast beamformin...
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02/19/2018
Learning Hidden Markov Models from Pairwise Co-occurrences with Applications to Topic Modeling
We present a new algorithm for identifying the transition and emission p...
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12/01/2017
Tensors, Learning, and 'Kolmogorov Extension' for Finite-alphabet Random Vectors
Estimating the joint probability mass function (PMF) of a set of random ...
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11/21/2017
Kullback-Leibler Principal Component for Tensors is not NP-hard
We study the problem of nonnegative rank-one approximation of a nonnegat...
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11/20/2017
On Convergence of Epanechnikov Mean Shift
Epanechnikov Mean Shift is a simple yet empirically very effective algor...
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09/02/2017
On Identifiability of Nonnegative Matrix Factorization
In this letter, we propose a new identification criterion that guarantee...
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02/16/2017
Completing a joint PMF from projections: a low-rank coupled tensor factorization approach
There has recently been considerable interest in completing a low-rank m...
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11/15/2016
Anchor-Free Correlated Topic Modeling: Identifiability and Algorithm
In topic modeling, many algorithms that guarantee identifiability of the...
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08/15/2016
Robust Volume Minimization-Based Matrix Factorization for Remote Sensing and Document Clustering
This paper considers volume minimization (VolMin)-based structured matri...
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07/06/2016
Tensor Decomposition for Signal Processing and Machine Learning
Tensors or multi-way arrays are functions of three or more indices (i,j...
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05/31/2016
Scalable and Flexible Multiview MAX-VAR Canonical Correlation Analysis
Generalized canonical correlation analysis (GCCA) aims at finding latent...
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05/21/2016
Learning From Hidden Traits: Joint Factor Analysis and Latent Clustering
Dimensionality reduction techniques play an essential role in data analy...
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06/13/2015
A Flexible and Efficient Algorithmic Framework for Constrained Matrix and Tensor Factorization
We propose a general algorithmic framework for constrained matrix and te...
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02/28/2013