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Sharan Vaswani
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2020 – today
- 2024
- [i26]Anh Dang, Reza Babanezhad, Sharan Vaswani:
Noise-adaptive (Accelerated) Stochastic Heavy-Ball Momentum. CoRR abs/2401.06738 (2024) - [i25]Saurabh Mishra, Anant Raj, Sharan Vaswani:
From Inverse Optimization to Feasibility to ERM. CoRR abs/2402.17890 (2024) - [i24]Michael Lu, Matin Aghaei, Anant Raj, Sharan Vaswani:
Towards Principled, Practical Policy Gradient for Bandits and Tabular MDPs. CoRR abs/2405.13136 (2024) - 2023
- [c18]Jonathan Wilder Lavington, Sharan Vaswani, Reza Babanezhad Harikandeh, Mark Schmidt, Nicolas Le Roux:
Target-based Surrogates for Stochastic Optimization. ICML 2023: 18614-18651 - [c17]Sharan Vaswani, Amirreza Kazemi, Reza Babanezhad Harikandeh, Nicolas Le Roux:
Decision-Aware Actor-Critic with Function Approximation and Theoretical Guarantees. NeurIPS 2023 - [i23]Jonathan Wilder Lavington, Sharan Vaswani, Reza Babanezhad, Mark Schmidt, Nicolas Le Roux:
Target-based Surrogates for Stochastic Optimization. CoRR abs/2302.02607 (2023) - [i22]Sharan Vaswani, Amirreza Kazemi, Reza Babanezhad, Nicolas Le Roux:
Decision-Aware Actor-Critic with Function Approximation and Theoretical Guarantees. CoRR abs/2305.15249 (2023) - 2022
- [j2]Benjamin Dubois-Taine
, Sharan Vaswani, Reza Babanezhad, Mark Schmidt, Simon Lacoste-Julien:
SVRG meets AdaGrad: painless variance reduction. Mach. Learn. 111(12): 4359-4409 (2022) - [c16]Sharan Vaswani, Olivier Bachem, Simone Totaro, Robert Müller, Shivam Garg, Matthieu Geist, Marlos C. Machado
, Pablo Samuel Castro, Nicolas Le Roux:
A general class of surrogate functions for stable and efficient reinforcement learning. AISTATS 2022: 8619-8649 - [c15]Jonathan Wilder Lavington, Sharan Vaswani, Mark Schmidt:
Improved Policy Optimization for Online Imitation Learning. CoLLAs 2022: 1146-1173 - [c14]Sharan Vaswani, Benjamin Dubois-Taine, Reza Babanezhad:
Towards Noise-adaptive, Problem-adaptive (Accelerated) Stochastic Gradient Descent. ICML 2022: 22015-22059 - [c13]Sharan Vaswani, Lin Yang, Csaba Szepesvári:
Near-Optimal Sample Complexity Bounds for Constrained MDPs. NeurIPS 2022 - [c12]Arushi Jain, Sharan Vaswani, Reza Babanezhad, Csaba Szepesváari, Doina Precup:
Towards painless policy optimization for constrained MDPs. UAI 2022: 895-905 - [i21]Arushi Jain, Sharan Vaswani, Reza Babanezhad, Csaba Szepesvári, Doina Precup:
Towards Painless Policy Optimization for Constrained MDPs. CoRR abs/2204.05176 (2022) - [i20]Sharan Vaswani, Lin F. Yang
, Csaba Szepesvári:
Near-Optimal Sample Complexity Bounds for Constrained MDPs. CoRR abs/2206.06270 (2022) - [i19]Jonathan Wilder Lavington, Sharan Vaswani, Mark Schmidt:
Improved Policy Optimization for Online Imitation Learning. CoRR abs/2208.00088 (2022) - 2021
- [c11]Nicolas Loizou, Sharan Vaswani, Issam Hadj Laradji, Simon Lacoste-Julien:
Stochastic Polyak Step-size for SGD: An Adaptive Learning Rate for Fast Convergence. AISTATS 2021: 1306-1314 - [i18]Benjamin Dubois-Taine, Sharan Vaswani, Reza Babanezhad, Mark Schmidt, Simon Lacoste-Julien:
SVRG Meets AdaGrad: Painless Variance Reduction. CoRR abs/2102.09645 (2021) - [i17]Sharan Vaswani, Olivier Bachem, Simone Totaro, Robert Mueller, Matthieu Geist, Marlos C. Machado, Pablo Samuel Castro, Nicolas Le Roux:
A functional mirror ascent view of policy gradient methods with function approximation. CoRR abs/2108.05828 (2021) - [i16]Sharan Vaswani, Benjamin Dubois-Taine, Reza Babanezhad:
Towards Noise-adaptive, Problem-adaptive Stochastic Gradient Descent. CoRR abs/2110.11442 (2021) - 2020
- [j1]Mohamed Osama Ahmed
, Sharan Vaswani, Mark Schmidt:
Combining Bayesian optimization and Lipschitz optimization. Mach. Learn. 109(1): 79-102 (2020) - [c10]Si Yi Meng, Sharan Vaswani, Issam Hadj Laradji, Mark Schmidt, Simon Lacoste-Julien:
Fast and Furious Convergence: Stochastic Second Order Methods under Interpolation. AISTATS 2020: 1375-1386 - [c9]Sharan Vaswani, Abbas Mehrabian, Audrey Durand, Branislav Kveton:
Old Dog Learns New Tricks: Randomized UCB for Bandit Problems. AISTATS 2020: 1988-1998 - [i15]Nicolas Loizou, Sharan Vaswani, Issam H. Laradji, Simon Lacoste-Julien:
Stochastic Polyak Step-size for SGD: An Adaptive Learning Rate for Fast Convergence. CoRR abs/2002.10542 (2020) - [i14]Sharan Vaswani, Reza Babanezhad, Jose Gallego, Aaron Mishkin, Simon Lacoste-Julien, Nicolas Le Roux:
To Each Optimizer a Norm, To Each Norm its Generalization. CoRR abs/2006.06821 (2020) - [i13]Sharan Vaswani, Frederik Kunstner, Issam H. Laradji, Si Yi Meng, Mark Schmidt, Simon Lacoste-Julien:
Adaptive Gradient Methods Converge Faster with Over-Parameterization (and you can do a line-search). CoRR abs/2006.06835 (2020)
2010 – 2019
- 2019
- [c8]Sharan Vaswani, Francis R. Bach, Mark Schmidt:
Fast and Faster Convergence of SGD for Over-Parameterized Models and an Accelerated Perceptron. AISTATS 2019: 1195-1204 - [c7]Branislav Kveton, Csaba Szepesvári, Sharan Vaswani, Zheng Wen, Tor Lattimore, Mohammad Ghavamzadeh:
Garbage In, Reward Out: Bootstrapping Exploration in Multi-Armed Bandits. ICML 2019: 3601-3610 - [c6]Sharan Vaswani, Aaron Mishkin, Issam H. Laradji, Mark Schmidt, Gauthier Gidel, Simon Lacoste-Julien:
Painless Stochastic Gradient: Interpolation, Line-Search, and Convergence Rates. NeurIPS 2019: 3727-3740 - [i12]Sharan Vaswani, Aaron Mishkin, Issam H. Laradji, Mark Schmidt, Gauthier Gidel, Simon Lacoste-Julien:
Painless Stochastic Gradient: Interpolation, Line-Search, and Convergence Rates. CoRR abs/1905.09997 (2019) - [i11]Si Yi Meng, Sharan Vaswani, Issam H. Laradji, Mark Schmidt, Simon Lacoste-Julien:
Fast and Furious Convergence: Stochastic Second Order Methods under Interpolation. CoRR abs/1910.04920 (2019) - [i10]Sharan Vaswani, Abbas Mehrabian, Audrey Durand, Branislav Kveton:
Old Dog Learns New Tricks: Randomized UCB for Bandit Problems. CoRR abs/1910.04928 (2019) - 2018
- [i9]Sharan Vaswani, Branislav Kveton, Zheng Wen, Anup Rao, Mark Schmidt, Yasin Abbasi-Yadkori:
New Insights into Bootstrapping for Bandits. CoRR abs/1805.09793 (2018) - [i8]Mohamed Osama Ahmed, Sharan Vaswani, Mark Schmidt:
Combining Bayesian Optimization and Lipschitz Optimization. CoRR abs/1810.04336 (2018) - [i7]Sharan Vaswani, Francis R. Bach, Mark Schmidt:
Fast and Faster Convergence of SGD for Over-Parameterized Models and an Accelerated Perceptron. CoRR abs/1810.07288 (2018) - 2017
- [c5]Sharan Vaswani, Mark Schmidt, Laks V. S. Lakshmanan:
Horde of Bandits using Gaussian Markov Random Fields. AISTATS 2017: 690-699 - [c4]Sharan Vaswani, Branislav Kveton, Zheng Wen, Mohammad Ghavamzadeh, Laks V. S. Lakshmanan, Mark Schmidt:
Model-Independent Online Learning for Influence Maximization. ICML 2017: 3530-3539 - [c3]Zheng Wen, Branislav Kveton, Michal Valko, Sharan Vaswani:
Online Influence Maximization under Independent Cascade Model with Semi-Bandit Feedback. NIPS 2017: 3022-3032 - [i6]Sharan Vaswani, Branislav Kveton, Zheng Wen, Mohammad Ghavamzadeh, Laks V. S. Lakshmanan, Mark Schmidt:
Diffusion Independent Semi-Bandit Influence Maximization. CoRR abs/1703.00557 (2017) - [i5]Sharan Vaswani, Mark Schmidt, Laks V. S. Lakshmanan:
Horde of Bandits using Gaussian Markov Random Fields. CoRR abs/1703.02626 (2017) - 2016
- [i4]Sharan Vaswani, Laks V. S. Lakshmanan:
Adaptive Influence Maximization in Social Networks: Why Commit when You can Adapt? CoRR abs/1604.08171 (2016) - 2015
- [i3]Sharan Vaswani, Laks V. S. Lakshmanan:
Influence Maximization with Bandits. CoRR abs/1503.00024 (2015) - 2014
- [c2]Vincent Yun Lou, Smriti Bhagat, Laks V. S. Lakshmanan, Sharan Vaswani:
Modeling non-progressive phenomena for influence propagation. COSN 2014: 131-138 - [i2]Vincent Yun Lou, Smriti Bhagat, Laks V. S. Lakshmanan, Sharan Vaswani:
Modeling Non-Progressive Phenomena for Influence Propagation. CoRR abs/1408.6466 (2014) - 2013
- [c1]Jyotsna Khemka, Mrugesh R. Gajjar, Sharan Vaswani, Naga Vydyanathan, Rama Malladi, Vinutha S. V:
Performance evaluation of medical imaging algorithms on Intel® MIC platform. HiPC 2013: 396-404 - [i1]Rahul Thota, Sharan Vaswani, Amit A. Kale, Nagavijayalakshmi Vydyanathan:
Fast 3D Salient Region Detection in Medical Images using GPUs. CoRR abs/1310.6736 (2013)
Coauthor Index
aka: Reza Babanezhad Harikandeh
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last updated on 2024-08-15 23:43 CEST by the dblp team
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