Honors & Awards


  • EDGE: Enhancing Diversity in Graduate Education Doctoral Fellowship, Stanford University, CA, USA (09/20/2021)
  • First Prize in Madhava Mathematics Competition, Tata Institute of Fundamental Research, India (03/24/2019)
  • Usri Gangopadhay Memorial Gold Medal, Indian Statistical Institute, Kolkata, India (01/23/2020)
  • Mukul Chaudhury Memorial Award, Indian Statistical Institute, Kolkata, India (01/10/2019)
  • Mukul Chaudhuri Memorial Award, Indian Statistical Institute, Kolkata, India (01/09/2018)

Education & Certifications


  • M.Stat, Indian Statistical Institute, Kolkata, India (2021)
  • B.Stat (Hons.), Indian Statistical Institute, Kolkata, India (2019)

All Publications


  • On Consistent Entropy-Regularized k-Means Clustering With Feature Weight Learning: Algorithm and Statistical Analyses. IEEE transactions on cybernetics Chakraborty, S., Paul, D., Das, S. 2022; PP

    Abstract

    Clusters in real data are often restricted to low-dimensional subspaces rather than the entire feature space. Recent approaches to circumvent this difficulty are often computationally inefficient and lack theoretical justification in terms of their large-sample behavior. This article deals with the problem by introducing an entropy incentive term to efficiently learn the feature importance within the framework of center-based clustering. A scalable block-coordinate descent algorithm, with closed-form updates, is incorporated to minimize the proposed objective function. We establish theoretical guarantees on our method by Vapnik-Chervonenkis (VC) theory to establish strong consistency along with uniform concentration bounds. The merits of our method are showcased through detailed experimental analysis on toy examples as well as real data clustering benchmarks.

    View details for DOI 10.1109/TCYB.2022.3166975

    View details for PubMedID 35609103

  • On the uniform concentration bounds and large sample properties of clustering with Bregman divergences STAT Paul, D., Chakraborty, S., Das, S. 2021; 10 (1)

    View details for DOI 10.1002/sta4.360

    View details for Web of Science ID 000634461800001

  • Automated Clustering of High-dimensional Data with a Feature Weighted Mean Shift Algorithm Chakraborty, S., Paul, D., Das, S., Assoc Advancement Artificial Intelligence ASSOC ADVANCEMENT ARTIFICIAL INTELLIGENCE. 2021: 6930-6938
  • t-Entropy: A New Measure of Uncertainty with Some Applications Chakraborty, S., Paul, D., Das, S., IEEE IEEE. 2021: 1475-1480
  • Uniform Concentration Bounds toward a Unified Framework for Robust Clustering Thirty-fifth Conference on Neural Information Processing Systems (NeurIPS), 2021. Paul, D., Chakraborty, S., Das, S., Xu, J. 2021
  • Hierarchical clustering with optimal transport STATISTICS & PROBABILITY LETTERS Chakraborty, S., Paul, D., Das, S. 2020; 163
  • Entropy Weighted Power k-Means Clustering Chakraborty, S., Paul, D., Das, S., Xu, J., Chiappa, S., Calandra, R. ADDISON-WESLEY PUBL CO. 2020: 691-700
  • A Bayesian non-parametric approach for automatic clustering with feature weighting STAT Paul, D., Das, S. 2020; 9 (1)

    View details for DOI 10.1002/sta4.306

    View details for Web of Science ID 000614806100049

  • A New Visual Cryptography Scheme with Perfect Contrast using Galois Fields Paul, D., Chakraborty, S., IEEE IEEE. 2019: 7-11
  • On the Non-convergence of Differential Evolution: Some Generalized Adversarial Conditions and A Remedy Paul, D., Chakraborty, S., Das, S., Zelinka, I., ACM ASSOC COMPUTING MACHINERY. 2019: 265-266