| Suspicion-free adversarial attacks on clustering algorithms A Roy, A Chhabra, P Mohapatra Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 3625-3632, 2020 | 28* | 2020 |
| Online and bandit algorithms for nonstationary stochastic saddle-point optimization A Roy, Y Chen, K Balasubramanian, P Mohapatra arXiv preprint arXiv:1912.01698, 2019 | 24 | 2019 |
| A moving target defense against adversarial machine learning A Roy, A Chhabra, CA Kamhoua, P Mohapatra Proceedings of the 4th ACM/IEEE Symposium on Edge Computing, 383-388, 2019 | 21 | 2019 |
| Stochastic Zeroth-Order Optimization under Nonstationarity and Nonconvexity A Roy, K Balasubramanian, S Ghadimi, P Mohapatra Journal of Machine Learning Research 2022, 2022 | 18* | 2022 |
| Stochastic Zeroth-order Discretizations of Langevin Diffusions for Bayesian Inference A Roy, L Shen, K Balasubramanian, S Ghadimi Bernoulli 2021 (to appear), 2019 | 15* | 2019 |
| On Empirical Risk Minimization with Dependent and Heavy-Tailed Data A Roy, K Balasubramanian, MA Erdogdu 35th Conference on Neural Information Processing Systems (NeurIPS 2021 …, 2021 | 13 | 2021 |
| Game Theoretic Characterization of Collusive Behavior among Attackers A Roy, CA Kamhoua, P Mohapatra IEEE INFOCOM 2018-IEEE Conference on Computer Communications, 2078-2086, 2018 | 8 | 2018 |
| Escaping saddle-point faster under interpolation-like conditions A Roy, K Balasubramanian, S Ghadimi, P Mohapatra Advances in Neural Information Processing Systems 33, 12414-12425, 2020 | 6 | 2020 |
| Constrained Stochastic Nonconvex Optimization with State-dependent Markov Data A Roy, K Balasubramanian, S Ghadimi Advances in Neural Information Processing Systems, 2022, 2022 | 4 | 2022 |
| Optimization on Pareto sets: On a theory of multi-objective optimization A Roy, G So, YA Ma arXiv preprint arXiv:2308.02145, 2023 | 3 | 2023 |
| Fairness Uncertainty Quantification: How certain are you that the model is fair? A Roy, P Mohapatra arXiv preprint arXiv:2304.13950, 2023 | 3 | 2023 |
| Online covariance estimation for stochastic gradient descent under Markovian sampling A Roy, K Balasubramanian arXiv preprint arXiv:2308.01481, 2023 | 2 | 2023 |
| A Central Limit Theorem for Stochastic Saddle Point Optimization A Roy, YA Ma arXiv preprint arXiv:2306.06305, 2023 | | 2023 |
Prasant MohapatraProfessor of Computer Science and Engineering, University of South FloridaVerified email at usf.edu
