Nicholas D. Sidiropoulos

research

∙ 05/06/2023

On High-dimensional and Low-rank Tensor Bandits

Most existing studies on linear bandits focus on the one-dimensional cha...

0 Chengshuai Shi, et al. ∙

research

∙ 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...

0 Nicholas D. Sidiropoulos, et al. ∙

research

∙ 10/13/2022

Learning Multivariate CDFs and Copulas using Tensor Factorization

Learning the multivariate distribution of data is a core challenge in st...

0 Magda Amiridi, et al. ∙

research

∙ 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...

0 Zack W. Almquist, et al. ∙

research

∙ 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...

8 Magda Amiridi, et al. ∙

research

∙ 03/18/2021

Probabilistic Simplex Component Analysis

This study presents PRISM, a probabilistic simplex component analysis ap...

0 Ruiyuan Wu, et al. ∙

research

∙ 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...

0 Aritra Konar, et al. ∙

research

∙ 12/20/2020

eTREE: Learning Tree-structured Embeddings

Matrix factorization (MF) plays an important role in a wide range of mac...

0 Faisal M. Almutairi, et al. ∙

research

∙ 12/08/2020

STELAR: Spatio-temporal Tensor Factorization with Latent Epidemiological Regularization

Accurate prediction of the transmission of epidemic diseases such as COV...

0 Nikos Kargas, et al. ∙

research

∙ 11/03/2020

GAGE: Geometry Preserving Attributed Graph Embeddings

Node representation learning is the task of extracting concise and infor...

0 Charilaos I. Kanatsoulis, et al. ∙

research

∙ 10/30/2020

Information-theoretic Feature Selection via Tensor Decomposition and Submodularity

Feature selection by maximizing high-order mutual information between th...

12 Magda Amiridi, et al. ∙

research

∙ 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...

0 Charilaos I. Kanatsoulis, et al. ∙

research

∙ 10/01/2020

PHASED: Phase-Aware Submodularity-Based Energy Disaggregation

Energy disaggregation is the task of discerning the energy consumption o...

0 Faisal M. Almutairi, et al. ∙

research

∙ 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...

3 Magda Amiridi, et al. ∙

research

∙ 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...

0 Aritra Konar, et al. ∙

research

∙ 03/27/2020

GRATE: Granular Recovery of Aggregated Tensor Data by Example

In this paper, we address the challenge of recovering an accurate breakd...

0 Ahmed S. Zamzam, et al. ∙

research

∙ 03/25/2020

Generalized Canonical Correlation Analysis: A Subspace Intersection Approach

Generalized Canonical Correlation Analysis (GCCA) is an important tool t...

0 Mikael Sørensen, et al. ∙

research

∙ 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...

0 Mohamed Salah Ibrahim, et al. ∙

research

∙ 10/26/2019

PREMA: Principled Tensor Data Recovery from Multiple Aggregated Views

Multidimensional data have become ubiquitous and are frequently involved...

0 Faisal M. Almutairi, et al. ∙

research

∙ 07/27/2019

REP: Predicting the Time-Course of Drug Sensitivity

The biological processes involved in a drug's mechanisms of action are o...

0 Cheng Qian, et al. ∙

research

∙ 06/13/2019

Nonlinear System Identification via Tensor Completion

Function approximation from input and output data pairs constitutes a fu...

0 Nikolaos Kargas, et al. ∙

research

∙ 04/28/2019

Machine Learning in the Air

Thanks to the recent advances in processing speed and data acquisition a...

12 Deniz Gündüz, et al. ∙

research

∙ 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...

0 Nikos Kargas, et al. ∙

research

∙ 03/26/2019

Energy Storage Management via Deep Q-Networks

Energy storage devices represent environmentally friendly candidates to ...

0 Ahmed S. Zamzam, et al. ∙

research

∙ 01/06/2019

Learning Nonlinear Mixtures: Identifiability and Algorithm

Linear mixture models have proven very useful in a plethora of applicati...

0 Xiao Fu, et al. ∙

research

∙ 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...

1 Cheng Qian, et al. ∙

research

∙ 09/22/2018

Coupled Graphs and Tensor Factorization for Recommender Systems and Community Detection

Joint analysis of data from multiple information repositories facilitate...

0 Vassilis N. Ioannidis, et al. ∙

research

∙ 04/24/2018

Structured SUMCOR Multiview Canonical Correlation Analysis for Large-Scale Data

The sum-of-correlations (SUMCOR) formulation of generalized canonical co...

0 Charilaos I. Kanatsoulis, et al. ∙

research

∙ 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...

0 Xiao Fu, et al. ∙

research

∙ 03/02/2018

Mirror-Prox SCA Algorithm for Multicast Beamforming and Antenna Selection

This paper considers the (NP-)hard problem of joint multicast beamformin...

0 Mohamed S. Ibrahim, et al. ∙

research

∙ 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...

0 Kejun Huang, et al. ∙

research

∙ 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 ...

0 Nikos Kargas, et al. ∙

research

∙ 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...

0 Kejun Huang, et al. ∙

research

∙ 11/20/2017

On Convergence of Epanechnikov Mean Shift

Epanechnikov Mean Shift is a simple yet empirically very effective algor...

0 Kejun Huang, et al. ∙

research

∙ 09/02/2017

On Identifiability of Nonnegative Matrix Factorization

In this letter, we propose a new identification criterion that guarantee...

0 Xiao Fu, et al. ∙

research

∙ 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...

0 Nikos Kargas, et al. ∙

research

∙ 11/15/2016

Anchor-Free Correlated Topic Modeling: Identifiability and Algorithm

In topic modeling, many algorithms that guarantee identifiability of the...

0 Kejun Huang, et al. ∙

research

∙ 08/15/2016

Robust Volume Minimization-Based Matrix Factorization for Remote Sensing and Document Clustering

This paper considers volume minimization (VolMin)-based structured matri...

0 Xiao Fu, et al. ∙

research

∙ 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...

0 Nicholas D. Sidiropoulos, et al. ∙

research

∙ 05/31/2016

Scalable and Flexible Multiview MAX-VAR Canonical Correlation Analysis

Generalized canonical correlation analysis (GCCA) aims at finding latent...

0 Xiao Fu, et al. ∙

research

∙ 05/21/2016

Learning From Hidden Traits: Joint Factor Analysis and Latent Clustering

Dimensionality reduction techniques play an essential role in data analy...

0 Xiao Fu, et al. ∙

research

∙ 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...

0 Kejun Huang, et al. ∙

research

∙ 02/28/2013

Scoup-SMT: Scalable Coupled Sparse Matrix-Tensor Factorization

How can we correlate neural activity in the human brain as it responds t...

0 Evangelos E. Papalexakis, et al. ∙

Nicholas D. Sidiropoulos

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