Papers

  1. Scalar Poincare implies Matrix Poincare with Ankit Garg and Nikhil Srivastava. Electronic Comunications in Probability (ECP) 2021
  2. A Potential Reduction Inspired Algorithm for Exact Max Flow in Almost O(m4/3) Time. Symposium on Foundations of Computer Science (FOCS) 2020
  3. A Faster Interior Point Method for Semidefinite Programming with Haotian Jiang, Yin Tat Lee, Swati Padmanabhan, Zhao Song. Symposium on Foundations of Computer Science (FOCS) 2020
  4. Algorithms for heavy-tailed statistics: regression, covariance estimation and beyond joint with Yeshwanth Cherpanamjeri, Samuel B. Hopkins, Prasad Raghavendra, Nilesh Tripuraneni. Symposium on Theory of Computing (STOC) 2020
  5. Fair and Diverse DPP-based Data Summarization joint with L. Elisa Celis, Vijay Keswani, Damian Straszak, Amit Deshpande, Nisheeth K. Vishnoi. International Conference on Machine Learning (ICML) 2018
  6. On the Complexity of Constrained Determinantal Point Processes joint with Damian Straszak, Amit Deshpande, L. Elisa Celis, Nisheeth K. Vishnoi. APPROX-RANDOM 2017
  7. Efficient and Provable Multi-Query Optimization joint with S. Sudarshan. Symposium on Principles of Database Systems (PODS) 2017
  8. Batched Gaussian Process Bandit Optimization via Determinantal Point Processes joint with Amit Deshpande, Pushmeet Kohli. Advances in Neural Information Processing Systems (NIPS) 2016
  9. How to be Fair and Diverse? joint with L. Elisa Celis, Amit Deshpande, Nisheeth K. Vishnoi. Workshop on Fairness, Accountability and Transparency in Machine Learning (FATML) 2016. (Oral)
  10. On Concentration Inequalities for Random Matrix Products joint with Satyaki Mukherjee, Nikhil Srivastava. 2020. Manuscript.
  11. A Matrix Bernstein Inequality for Strong Rayleigh Distributions. 2020. Manuscript.