most citedEntropy Regularized Power k-Means Clustering

2 citations · 5 across the 4 of their papers we have counts for

collaborators

6 papers

stat.ML20212 cited

Uniform Concentration Bounds toward a Unified Framework for Robust Clustering

Debolina Paul, Saptarshi Chakraborty, Swagatam Das +1

Recent advances in center-based clustering continue to improve upon the drawbacks of Lloyd's celebrated -means algorithm over years after its introduction. Various methods…

stat.ML20211 cited

Statistical Regeneration Guarantees of the Wasserstein Autoencoder with Latent Space Consistency

Anish Chakrabarty, Swagatam Das

The introduction of Variational Autoencoders (VAE) has been marked as a breakthrough in the history of representation learning models. Besides having several accolades of its own,…

cs.IT2021

t-Entropy: A New Measure of Uncertainty with Some Applications

Saptarshi Chakraborty, Debolina Paul, Swagatam Das

The concept of Entropy plays a key role in Information Theory, Statistics, and Machine Learning.This paper introduces a new entropy measure, called the t-entropy, which exploits th…

cs.SD2021

An Adaptive Learning based Generative Adversarial Network for One-To-One Voice Conversion

Sandipan Dhar, Nanda Dulal Jana, Swagatam Das

Voice Conversion (VC) emerged as a significant domain of research in the field of speech synthesis in recent years due to its emerging application in voice-assisting technology, au…

cs.LG2020

Automated Clustering of High-dimensional Data with a Feature Weighted Mean Shift Algorithm

Saptarshi Chakraborty, Debolina Paul, Swagatam Das

Mean shift is a simple interactive procedure that gradually shifts data points towards the mode which denotes the highest density of data points in the region. Mean shift algorithm…

stat.ML20202 cited

Entropy Regularized Power k-Means Clustering

Saptarshi Chakraborty, Debolina Paul, Swagatam Das +1

Despite its well-known shortcomings, -means remains one of the most widely used approaches to data clustering. Current research continues to tackle its flaws while attempting to…