Publications & Preprints
(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). To appear. Paper
(2025) Minimax Rates for Distribution Estimation on Low-dimensional Spaces. Saptarshi Chakraborty. Transactions on Machine Learning Research (TMLR) Paper
(2024) A Statistical Analysis of Deep Federated Learning for Intrinsically Low-dimensional Data. Saptarshi Chakraborty and Peter Bartlett. arXiv
(2024) On the Statistical Properties of Generative Adversarial Models for Low Intrinsic Data Dimension. 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. International Conference on Artificial Intelligence and Statistics (AISTATS). Paper Github.
(2022) Bregman Power k-Means for Clustering Exponential Family Data. Adithya Vellal, Saptarshi Chakraborty and Jason Xu. International Conference on Machine Learning (ICML). Paper Github.
(2022) Implicit Annealing in Kernel Spaces: A Strongly Consistent Clustering Approach. Debolina Paul, Saptarshi Chakraborty, Swagatam Das and Jason Xu. IEEE Transactions on Pattern Analysis and Machine Intelligence (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. Neural Information Processing Systems (NeurIPS). Paper
(2021) On Uniform Concentration Bounds for Bi-clustering by using the Vapnik-Chervonenkis Theory. Saptarshi Chakraborty, and Swagatam Das. Statistics and Probability Letters. Paper
(2021) Automated Clustering of High-dimensional Data with a Feature Weighted Mean-shift Algorithm. Saptarshi Chakraborty, Debolina Paul and Swagatam Das. AAAI Conference on Artificial Intelligence (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 Transactions on Pattern Analysis and Machine Intelligence (TPAMI). Paper Github.
(2020) Entropy Weighted Power k-Means Clustering. Saptarshi Chakraborty, Debolina Paul, Swagatam Das and Jason Xu. International Conference on Artificial Intelligence and Statistics (AISTATS). Paper arXiv.
(2020) Hierarchical Clustering with Optimal Transport Statistics and Probability Letters. Saptarshi Chakraborty, Debolina Paul and Swagatam Das. Statistics and Probability Letters. Paper.
(2019) On the strong consistency of feature-weighted k-means clustering in a nearmetric space. Saptarshi Chakraborty and Swagatam Das. Stat. Paper.
(2019) On the non-convergence of differential evolution: some generalized adversarial conditions and a remedy. Debolina Paul, Saptarshi Chakraborty, Swagatam Das and Ivan Zelinka. Genetic and Evolutionary Computation Conference Companion (GECCO). Paper.
(2018) Simultaneous variable weighting and determining the number of clusters—A weighted Gaussian means algorithm. Sapatarshi 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.