Publications & Preprints

(2026) Convex Clustering Redefined: Robust Learning With the Median of Means Estimator. Koustav Chowdhury, Bibhabasu Mandal, Sourav De, Sagar Ghosh, Swagatam Das, Debolina Paul, Saptarshi Chakraborty. AAAI, 2026. To appear.

(2025) On the Statistical Properties of Generative Adversarial Models for Low Intrinsic Data Dimension.
Saptarshi Chakraborty and Peter Bartlett. Journal of Machine Learning Research (JMLR).
arXiv   Paper

(2025) Statistical Guarantees for Unpaired Image-to-Image Cross-Domain Analysis using GANs.
Saptarshi Chakraborty and Peter Bartlett. International Conference on Artificial Intelligence and Statistics (AISTATS).
Paper

(2025) Minimax Rates for Distribution Estimation on Low-dimensional Spaces.
Saptarshi Chakraborty. Transactions on Machine Learning Research (TMLR).
Paper

(2024) A Statistical Analysis for Supervised Deep Learning with Exponential Families for Intrinsically Low-dimensional Data.
Saptarshi Chakraborty and Peter Bartlett.
arXiv

(2024) A Statistical Analysis of Deep Federated Learning for Intrinsically Low-dimensional Data.
Saptarshi Chakraborty and Peter Bartlett.
arXiv

(2024) A Statistical Analysis of Wasserstein Autoencoders for Intrinsically Low-dimensional Data.
Saptarshi Chakraborty and Peter Bartlett. International Conference on Learning Representations (ICLR).
Paper   arXiv   Github

(2023) Biconvex Clustering.
Saptarshi Chakraborty and Jason Xu. Journal of Computational and Graphical Statistics.
Paper   arXiv   Github

(2023) Robust Principal Component Analysis: A Median of Means Approach.
Debolina Paul, Saptarshi Chakraborty and Swagatam Das. IEEE Transactions on Neural Networks and Learning Systems.
Paper

(2023) Clustering High-dimensional Data with Ordered Weighted L1 Regularization.
Chandramouli Chakraborty, Sayan Paul, Saptarshi Chakraborty, and Swagatam Das. AISTATS.
Paper   Github

(2022) Bregman Power k-Means for Clustering Exponential Family Data.
Adithya Vellal, Saptarshi Chakraborty and Jason Xu. ICML.
Paper   Github

(2022) Implicit Annealing in Kernel Spaces: A Strongly Consistent Clustering Approach.
Debolina Paul, Saptarshi Chakraborty, Swagatam Das and Jason Xu. IEEE TPAMI.
Paper

(2022) A Consistent Entropy-Regularized Weighted k-Means Clustering Algorithm.
Debolina Paul, Saptarshi Chakraborty, and Swagatam Das. IEEE Transactions on Cybernetics.
Paper

(2021) Uniform Concentration Bounds toward a Unified Framework for Robust Clustering.
Debolina Paul, Saptarshi Chakraborty, Swagatam Das and Jason Xu. NeurIPS.
Paper

(2021) On Uniform Concentration Bounds for Bi-clustering using VC Theory.
Saptarshi Chakraborty and Swagatam Das. Statistics and Probability Letters.
Paper

(2021) $t$-Entropy: A New Measure of Uncertainty with Some Applications.
Saptarshi Chakraborty, Debolina Paul and Swagatam Das. ISIT.
Paper   arXiv   Github

(2021) Automated Clustering of High-dimensional Data with a Feature Weighted Mean-shift Algorithm.
Saptarshi Chakraborty, Debolina Paul and Swagatam Das. AAAI.
Paper   arXiv   Github

(2021) On the Uniform Concentration Bounds and Large Sample Properties of Clustering with Bregman Divergences.
Debolina Paul, Saptarshi Chakraborty and Swagatam Das. Stat.
Paper

(2021) Detecting Meaningful Clusters from High-dimensional Data: A Strongly Consistent Sparse Center-based Clustering Approach.
Saptarshi Chakraborty and Swagatam Das. IEEE TPAMI.
Paper   Github

(2020) Entropy Weighted Power k-Means Clustering.
Saptarshi Chakraborty, Debolina Paul, Swagatam Das and Jason Xu. AISTATS.
Paper   arXiv

(2020) Hierarchical Clustering with Optimal Transport.
Saptarshi Chakraborty, Debolina Paul and Swagatam Das. Statistics and Probability Letters.
Paper

(2019) On the Strong Consistency of Feature-weighted k-means in Near-metric Spaces.
Saptarshi Chakraborty and Swagatam Das. Stat.
Paper

(2019) On the Non-convergence of Differential Evolution: Adversarial Conditions and a Remedy.
Debolina Paul, Saptarshi Chakraborty, Swagatam Das and Ivan Zelinka. GECCO Companion.
Paper

(2018) Simultaneous Variable Weighting and Determining the Number of Clusters — A Weighted Gaussian Means Algorithm.
Saptarshi Chakraborty and Swagatam Das. Statistics and Probability Letters.
Paper   Github

(2017) k-Means Clustering with a New Divergence-based Distance Metric: Convergence and Performance Analysis.
Saptarshi Chakraborty and Swagatam Das. Pattern Recognition Letters.
Paper   Github