activity
20152026
most citedReal-time Dynamic MRI Reconstruction using Stacked Denoising Autoencoder

13 citations · 49 across the 57 of their papers we have counts for

collaborators
Showing cs.LGShow all

14 papers · 1 filter

cs.LG2026

Median-of-Means as an Extremal Convex Estimator and a Nonconvex Route to the Trimmed Oracle

Angshul Majumdar

We revisit median-of-means estimation from a deterministic optimization viewpoint and develop a family of block-Lp estimators for robust learning with heavy-tailed and adversariall…

cs.LG2025

Dictionary-Transform Generative Adversarial Networks

Angshul Majumdar

Generative adversarial networks (GANs) are widely used for distribution learning, yet their classical formulations remain theoretically fragile, with ill-posed objectives, unstable…

cs.LG2025

A Unified Matrix Factorization Framework for Classical and Robust Clustering

Angshul Majumdar

This paper presents a unified matrix factorization framework for classical and robust clustering. We begin by revisiting the well-known equivalence between crisp k-means clustering…

cs.LG2020★ 11 cited

DeConFuse : A Deep Convolutional Transform based Unsupervised Fusion Framework

Pooja Gupta, Jyoti Maggu, Angshul Majumdar +2

This work proposes an unsupervised fusion framework based on deep convolutional transform learning. The great learning ability of convolutional filters for data analysis is well ac…

cs.LG2020

ConFuse: Convolutional Transform Learning Fusion Framework For Multi-Channel Data Analysis

Pooja Gupta, Jyoti Maggu, Angshul Majumdar +2

This work addresses the problem of analyzing multi-channel time series data %. In this paper, we by proposing an unsupervised fusion framework based on %the recently proposed convo…

cs.LG2020

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…