607 citations · 1.2k across the 34 of their papers we have counts for
39 papers
On High-dimensional and Low-rank Tensor Bandits
Chengshuai Shi, Cong Shen, Nicholas D. Sidiropoulos
Most existing studies on linear bandits focus on the one-dimensional characterization of the overall system. While being representative, this formulation may fail to model applicat…
Multisubject Task-Related fMRI Data Processing via a Two-Stage Generalized Canonical Correlation Analysis
Paris A. Karakasis, Athanasios P. Liavas, Nicholas D. Sidiropoulos +2
Functional magnetic resonance imaging (fMRI) is one of the most popular methods for studying the human brain. Task-related fMRI data processing aims to determine which brain areas…
Learning Multivariate CDFs and Copulas using Tensor Factorization
Magda Amiridi, Nicholas D. Sidiropoulos
Learning the multivariate distribution of data is a core challenge in statistics and machine learning. Traditional methods aim for the probability density function (PDF) and are li…
Minimizing low-rank models of high-order tensors: Hardness, span, tight relaxation, and applications
Nicholas D. Sidiropoulos, Paris Karakasis, Aritra Konar
We consider the problem of finding the smallest or largest entry of a tensor of order N that is specified via its rank decomposition. Stated in a different way, we are given N sets…
Uncovering migration systems through spatio-temporal tensor co-clustering
Zack W. Almquist, Tri Duc Nguyen, Mikael Sorensen +2
A central problem in the study of human mobility is that of migration systems. Typically, migration systems are defined as a set of relatively stable movements of people between tw…
Low-rank Characteristic Tensor Density Estimation Part II: Compression and Latent Density Estimation
Magda Amiridi, Nikos Kargas, Nicholas D. Sidiropoulos
Learning generative probabilistic models is a core problem in machine learning, which presents significant challenges due to the curse of dimensionality. This paper proposes a join…