8 citations · 19 across the 12 of their papers we have counts for
14 papers
A Central Limit Theorem for Intrinsic Fréchet Means on Real Grassmannians
Bipayan Banerjee, Imon Banerjee, Swagatam Das
Subspace-valued data arise in dimension reduction, image-set and video recognition, and signal processing, and the Fréchet mean is their standard sample mean [11,9,15,23]. We estab…
Coronal Heating as Determined by the Solar Flare Frequency Distribution Obtained by Aggregating Case Studies
James Paul Mason, Alexandra Werth, Colin G. West +999
Flare frequency distributions represent a key approach to addressing one of the largest problems in solar and stellar physics: determining the mechanism that counter-intuitively he…
Hybrid Gromov-Wasserstein Embedding for Capsule Learning
Pourya Shamsolmoali, Masoumeh Zareapoor, Swagatam Das +2
Capsule networks (CapsNets) aim to parse images into a hierarchy of objects, parts, and their relations using a two-step process involving part-whole transformation and hierarchica…
GridShift: A Faster Mode-seeking Algorithm for Image Segmentation and Object Tracking
Abhishek Kumar, Oladayo S. Ajani, Swagatam Das +1
In machine learning and computer vision, mean shift (MS) qualifies as one of the most popular mode-seeking algorithms used for clustering and image segmentation. It iteratively mov…
Interval Bound Interpolation for Few-shot Learning with Few Tasks
Shounak Datta, Sankha Subhra Mullick, Anish Chakrabarty +1
Few-shot learning aims to transfer the knowledge acquired from training on a diverse set of tasks to unseen tasks from the same task distribution with a limited amount of labeled d…
Robust Linear Predictions: Analyses of Uniform Concentration, Fast Rates and Model Misspecification
Saptarshi Chakraborty, Debolina Paul, Swagatam Das
The problem of linear predictions has been extensively studied for the past century under pretty generalized frameworks. Recent advances in the robust statistics literature allow u…
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…
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,…
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…
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…
Robust Principal Component Analysis: A Median of Means Approach
Debolina Paul, Saptarshi Chakraborty, Swagatam Das
Principal Component Analysis (PCA) is a fundamental tool for data visualization, denoising, and dimensionality reduction. It is widely popular in Statistics, Machine Learning, Comp…
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…
A Black-box Adversarial Attack Strategy with Adjustable Sparsity and Generalizability for Deep Image Classifiers
Arka Ghosh, Sankha Subhra Mullick, Shounak Datta +3
Constructing adversarial perturbations for deep neural networks is an important direction of research. Crafting image-dependent adversarial perturbations using white-box feedback h…
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…