k− Means clustering with a new divergence-based distance metric: Convergence and performance analysis S Chakraborty, S Das
Pattern Recognition Letters 100, 67-73, 2017
75 2017 Entropy weighted power k-means clustering S Chakraborty, D Paul, S Das, J Xu
International conference on artificial intelligence and statistics, 691-701, 2020
74 2020 Detecting meaningful clusters from high-dimensional data: A strongly consistent sparse center-based clustering approach S Chakraborty, S Das
IEEE Transactions on Pattern Analysis and Machine Intelligence 44 (6), 2894-2908, 2020
48 2020 Hierarchical clustering with optimal transport S Chakraborty, D Paul, S Das
Statistics & Probability Letters 163, 108781, 2020
43 2020 Simultaneous variable weighting and determining the number of clusters—A weighted Gaussian means algorithm S Chakraborty, S Das
Statistics & Probability Letters 137, 148-156, 2018
35 2018 Automated clustering of high-dimensional data with a feature weighted mean shift algorithm S Chakraborty, D Paul, S Das
Proceedings of the AAAI conference on artificial intelligence 35 (8), 6930-6938, 2021
20 2021 Uniform concentration bounds toward a unified framework for robust clustering D Paul, S Chakraborty, S Das, J Xu
Advances in Neural Information Processing Systems 34, 8307-8319, 2021
19 2021 Robust principal component analysis: A median of means approach D Paul, S Chakraborty, S Das
IEEE Transactions on Neural Networks and Learning Systems, 2023
14 2023 Implicit annealing in kernel spaces: A strongly consistent clustering approach D Paul, S Chakraborty, S Das, J Xu
IEEE Transactions on Pattern Analysis and Machine Intelligence 45 (5), 5862-5871, 2022
13 * 2022 On the strong consistency of feature‐weighted k ‐means clustering in a nearmetric space S Chakraborty, S Das
Stat 8 (1), e227, 2019
13 2019 Biconvex clustering S Chakraborty, J Xu
Journal of Computational and Graphical Statistics 32 (4), 1524-1536, 2023
11 2023 On the statistical properties of generative adversarial models for low intrinsic data dimension S Chakraborty, PL Bartlett
arXiv preprint arXiv:2401.15801, 2024
8 2024 On the uniform concentration bounds and large sample properties of clustering with Bregman divergences D Paul, S Chakraborty, S Das
Stat 10 (1), e360, 2021
8 2021 On consistent entropy-regularized k-means clustering with feature weight learning: Algorithm and statistical analyses S Chakraborty, D Paul, S Das
IEEE Transactions on Cybernetics 53 (8), 4779-4790, 2022
7 2022 S Chakraborty, D Paul, S Das
2021 IEEE International Symposium on Information Theory (ISIT), 1475-1480, 2021
7 2021 Bregman power k-means for clustering exponential family data A Vellal, S Chakraborty, JQ Xu
International Conference on Machine Learning, 22103-22119, 2022
5 2022 On uniform concentration bounds for bi-clustering by using the Vapnik–Chervonenkis theory S Chakraborty, S Das
Statistics & Probability Letters 175, 109102, 2021
4 2021 Principal Ellipsoid Analysis (PEA): Efficient non-linear dimension reduction & clustering D Paul, S Chakraborty, D Li, D Dunson
arXiv preprint arXiv:2008.07110, 2020
3 2020 A Statistical Analysis of Wasserstein Autoencoders for Intrinsically Low-dimensional Data S Chakraborty, P Bartlett
The Twelfth International Conference on Learning Representations, 2024
1 2024 Clustering High-dimensional Data with Ordered Weighted C Chakraborty, S Paul, S Chakraborty, S Das
International Conference on Artificial Intelligence and Statistics, 7176-7189, 2023
1 2023 
Swagatam DasProfessor, Electronics and Communication Sciences Unit, Indian Statistical Institute, Kolkataبريد إلكتروني تم التحقق منه على isical.ac.in
