| Stochastic approximation for canonical correlation analysis R Arora, TV Marinov, P Mianjy, N Srebro arXiv preprint arXiv:1702.06818, 2017 | 31 | 2017 |
| Stochastic optimization for multiview representation learning using partial least squares R Arora, P Mianjy, T Marinov International Conference on Machine Learning, 1786-1794, 2016 | 27 | 2016 |
| Streaming Kernel PCA with Random Features E Ullah, P Mianjy, TV Marinov, R Arora arXiv preprint arXiv:1808.00934, 2018 | 26 | 2018 |
| Streaming Kernel PCA with Random Features E Ullah, P Mianjy, TV Marinov, R Arora arXiv preprint arXiv:1808.00934, 2018 | 26 | 2018 |
| Corralling stochastic bandit algorithms R Arora, TV Marinov, M Mohri International Conference on Artificial Intelligence and Statistics, 2116-2124, 2021 | 24 | 2021 |
| Bandits with feedback graphs and switching costs R Arora, TV Marinov, M Mohri Advances in Neural Information Processing Systems 32, 10397-10407, 2019 | 17 | 2019 |
| Streaming principal component analysis in noisy setting TV Marinov, P Mianjy, R Arora International Conference on Machine Learning, 3413-3422, 2018 | 16 | 2018 |
| Beyond Value-Function Gaps: Improved Instance-Dependent Regret Bounds for Episodic Reinforcement Learning C Dann, TV Marinov, M Mohri, J Zimmert arXiv preprint arXiv:2107.01264, 2021 | 11 | 2021 |
| Policy regret in repeated games R Arora, M Dinitz, TV Marinov, M Mohri arXiv preprint arXiv:1811.04127, 2018 | 8 | 2018 |
| The Pareto Frontier of model selection for general Contextual Bandits TV Marinov, J Zimmert arXiv preprint arXiv:2110.13282, 2021 | 7 | 2021 |
| Efficient convex relaxations for streaming PCA R Arora, TV Marinov Advances in Neural Information Processing Systems 32, 10496-10505, 2019 | 4 | 2019 |
| COMPETING AGAINST ADAPTIVE AGENTS BY MINIMIZING COUNTERFACTUAL NOTIONS OF REGRET TV Marinov Johns Hopkins University, 2021 | | 2021 |
| Eulerian Orientations versus Euler Tours TV Marinov | | |
