11 papers
Deep Convolutional Transform Learning -- Extended version
Jyoti Maggu, Angshul Majumdar, Emilie Chouzenoux +1
This work introduces a new unsupervised representation learning technique called Deep Convolutional Transform Learning (DCTL). By stacking convolutional transforms, our approach is…
A computational approach to aid clinicians in selecting anti-viral drugs for COVID-19 trials
Aanchal Mongia, Sanjay Kr. Saha, Emilie Chouzenoux +1
COVID-19 has fast-paced drug re-positioning for its treatment. This work builds computational models for the same. The aim is to assist clinicians with a tool for selecting prospec…
Block Distributed Majorize-Minimize Memory Gradient Algorithm and its application to 3D image restoration
Mathieu Chalvidal, Emilie Chouzenoux
Modern 3D image recovery problems require powerful optimization frameworks to handle high dimensionality while providing reliable numerical solutions in a reasonable time. In this…
GraphEM: EM algorithm for blind Kalman filtering under graphical sparsity constraints
Émilie Chouzenoux, Víctor Elvira
Modeling and inference with multivariate sequences is central in a number of signal processing applications such as acoustics, social network analysis, biomedical, and finance, to…
Deep Latent Factor Model for Collaborative Filtering
Aanchal Mongia, Neha Jhamb, Emilie Chouzenoux +1
Latent factor models have been used widely in collaborative filtering based recommender systems. In recent years, deep learning has been successful in solving a wide variety of mac…
Transformed Subspace Clustering
Jyoti Maggu, Angshul Majumdar, Emilie Chouzenoux
Subspace clustering assumes that the data is sepa-rable into separate subspaces. Such a simple as-sumption, does not always hold. We assume that, even if the raw data is not separa…