45 citations · 113 across the 10 of their papers we have counts for
11 papers
Analysis and Utilization of Entrainment on Acoustic and Emotion Features in User-agent Dialogue
Daxin Tan, Nikos Kargas, David McHardy +6
Entrainment is the phenomenon by which an interlocutor adapts their speaking style to align with their partner in conversations. It has been found in different dimensions as acoust…
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…
Multi-version Tensor Completion for Time-delayed Spatio-temporal Data
Cheng Qian, Nikos Kargas, Cao Xiao +3
Real-world spatio-temporal data is often incomplete or inaccurate due to various data loading delays. For example, a location-disease-time tensor of case counts can have multiple d…
STELAR: Spatio-temporal Tensor Factorization with Latent Epidemiological Regularization
Nikos Kargas, Cheng Qian, Nicholas D. Sidiropoulos +3
Accurate prediction of the transmission of epidemic diseases such as COVID-19 is crucial for implementing effective mitigation measures. In this work, we develop a tensor method to…
Information-theoretic Feature Selection via Tensor Decomposition and Submodularity
Magda Amiridi, Nikos Kargas, Nicholas D. Sidiropoulos
Feature selection by maximizing high-order mutual information between the selected feature vector and a target variable is the gold standard in terms of selecting the best subset o…
Low-rank Characteristic Tensor Density Estimation Part I: Foundations
Magda Amiridi, Nikos Kargas, Nicholas D. Sidiropoulos
Effective non-parametric density estimation is a key challenge in high-dimensional multivariate data analysis. In this paper,we propose a novel approach that builds upon tensor fac…
Crowdsourcing via Pairwise Co-occurrences: Identifiability and Algorithms
Shahana Ibrahim, Xiao Fu, Nikos Kargas +1
The data deluge comes with high demands for data labeling. Crowdsourcing (or, more generally, ensemble learning) techniques aim to produce accurate labels via integrating noisy, no…
Nonlinear System Identification via Tensor Completion
Nikos Kargas, Nicholas D. Sidiropoulos
Function approximation from input and output data pairs constitutes a fundamental problem in supervised learning. Deep neural networks are currently the most popular method for lea…
Learning Mixtures of Smooth Product Distributions: Identifiability and Algorithm
Nikos Kargas, Nicholas D. Sidiropoulos
We study the problem of learning a mixture model of non-parametric product distributions. The problem of learning a mixture model is that of finding the component distributions alo…
Tensors, Learning, and 'Kolmogorov Extension' for Finite-alphabet Random Vectors
Nikos Kargas, Nicholas D. Sidiropoulos, Xiao Fu
Estimating the joint probability mass function (PMF) of a set of random variables lies at the heart of statistical learning and signal processing. Without structural assumptions, s…
Completing a joint PMF from projections: a low-rank coupled tensor factorization approach
Nikos Kargas, Nicholas D. Sidiropoulos
There has recently been considerable interest in completing a low-rank matrix or tensor given only a small fraction (or few linear combinations) of its entries. Related approaches…