Search Results for author: Nikos Kargas

Found 11 papers, 1 papers with code

Low-rank Characteristic Tensor Density Estimation Part II: Compression and Latent Density Estimation

1 code implementation20 Jun 2021 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.

Anomaly Detection Density Estimation +1

Multi-version Tensor Completion for Time-delayed Spatio-temporal Data

no code implementations11 May 2021 Cheng Qian, Nikos Kargas, Cao Xiao, Lucas Glass, Nicholas Sidiropoulos, Jimeng Sun

Recovering such missing or noisy (under-reported) elements of the input tensor can be viewed as a generalized tensor completion problem.

Missing Elements

STELAR: Spatio-temporal Tensor Factorization with Latent Epidemiological Regularization

no code implementations8 Dec 2020 Nikos Kargas, Cheng Qian, Nicholas D. Sidiropoulos, Cao Xiao, Lucas M. Glass, Jimeng Sun

Accurate prediction of the transmission of epidemic diseases such as COVID-19 is crucial for implementing effective mitigation measures.

Information-theoretic Feature Selection via Tensor Decomposition and Submodularity

no code implementations30 Oct 2020 Magda Amiridi, Nikos Kargas, Nicholas D. Sidiropoulos

By indirectly aiming to predict the latent variable of the naive Bayes model instead of the original target variable, it is possible to formulate the feature selection problem as maximization of a monotone submodular function subject to a cardinality constraint - which can be tackled using a greedy algorithm that comes with performance guarantees.

Combinatorial Optimization feature selection +1

Nonlinear System Identification via Tensor Completion

no code implementations13 Jun 2019 Nikos Kargas, Nicholas D. Sidiropoulos

Deep neural networks are currently the most popular method for learning to mimic the input-output relationship of a general nonlinear system, as they have proven to be very effective in approximating complex highly nonlinear functions.

Learning Mixtures of Smooth Product Distributions: Identifiability and Algorithm

no code implementations2 Apr 2019 Nikos Kargas, Nicholas D. Sidiropoulos

We study the problem of learning a mixture model of non-parametric product distributions.

Tensors, Learning, and 'Kolmogorov Extension' for Finite-alphabet Random Vectors

no code implementations1 Dec 2017 Nikos Kargas, Nicholas D. Sidiropoulos, Xiao Fu

This paper shows, perhaps surprisingly, that if the joint PMF of any three variables can be estimated, then the joint PMF of all the variables can be provably recovered under relatively mild conditions.

Movie Recommendation

Completing a joint PMF from projections: a low-rank coupled tensor factorization approach

no code implementations16 Feb 2017 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.

Recommendation Systems

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