Vaswani, Sharan

32 publications

TMLR 2025 (Accelerated) Noise-Adaptive Stochastic Heavy-Ball Momentum Anh Quang Dang, Reza Babanezhad Harikandeh, Sharan Vaswani

ICML 2025 Armijo Line-Search Can Make (Stochastic) Gradient Descent Provably Faster Sharan Vaswani, Reza Babanezhad Harikandeh

AISTATS 2025 Fast Convergence of SoftMax Policy Mirror Ascent Reza Asad, Reza Babanezhad Harikandeh, Issam H. Laradji, Nicolas Le Roux, Sharan Vaswani

NeurIPSW 2024 Fast Convergence of SoftMax Policy Mirror Ascent for Bandits & Tabular MDPs Reza Asad, Reza Babanezhad Harikandeh, Issam H. Laradji, Nicolas Le Roux, Sharan Vaswani

ICML 2024 From Inverse Optimization to Feasibility to ERM Saurabh Kumar Mishra, Anant Raj, Sharan Vaswani

NeurIPSW 2024 Improving OOD Generalization of Pre-Trained Encoders via Aligned Embedding-Space Ensembles Shuman Peng, Arash Khoeini, Sharan Vaswani, Martin Ester

NeurIPSW 2024 Improving OOD Generalization of Pre-Trained Encoders via Aligned Embedding-Space Ensembles Shuman Peng, Arash Khoeini, Sharan Vaswani, Martin Ester

NeurIPS 2024 Small Steps No More: Global Convergence of Stochastic Gradient Bandits for Arbitrary Learning Rates Jincheng Mei, Bo Dai, Alekh Agarwal, Sharan Vaswani, Anant Raj, Csaba Szepesvári, Dale Schuurmans

NeurIPS 2023 Decision-Aware Actor-Critic with Function Approximation and Theoretical Guarantees Sharan Vaswani, Amirreza Kazemi, Reza Babanezhad Harikandeh, Nicolas Le Roux

NeurIPSW 2023 MSL: An Adaptive Momentem-Based Stochastic Line-Search Framework Chen Fan, Sharan Vaswani, Christos Thrampoulidis, Mark Schmidt

NeurIPSW 2023 Noise-Adaptive (Accelerated) Stochastic Heavy-Ball Momentum Anh Quang Dang, Reza Babanezhad Harikandeh, Sharan Vaswani

NeurIPSW 2023 Practical Principled Policy Optimization for Finite MDPs Michael Lu, Matin Aghaei, Anant Raj, Sharan Vaswani

NeurIPSW 2023 Reducing Predict and Optimize to Convex Feasibility Saurabh kumar Mishra, Sharan Vaswani

NeurIPSW 2023 Surrogate Minimization: An Optimization Algorithm for Training Large Neural Networks with Model Parallelism Reza Asad, Reza Babanezhad Harikandeh, Issam H. Laradji, Nicolas Le Roux, Sharan Vaswani

ICML 2023 Target-Based Surrogates for Stochastic Optimization Jonathan Wilder Lavington, Sharan Vaswani, Reza Babanezhad Harikandeh, Mark Schmidt, Nicolas Le Roux

AISTATS 2022 A General Class of Surrogate Functions for Stable and Efficient Reinforcement Learning Sharan Vaswani, Olivier Bachem, Simone Totaro, Robert Müller, Shivam Garg, Matthieu Geist, Marlos C. Machado, Pablo Samuel Castro, Nicolas Le Roux

CoLLAs 2022 Improved Policy Optimization for Online Imitation Learning Jonathan Wilder Lavington, Sharan Vaswani, Mark Schmidt

NeurIPS 2022 Near-Optimal Sample Complexity Bounds for Constrained MDPs Sharan Vaswani, Lin Yang, Csaba Szepesvari

MLJ 2022 SVRG Meets AdaGrad: Painless Variance Reduction Benjamin Dubois-Taine, Sharan Vaswani, Reza Babanezhad, Mark Schmidt, Simon Lacoste-Julien

NeurIPSW 2022 Target-Based Surrogates for Stochastic Optimization Jonathan Wilder Lavington, Sharan Vaswani, Reza Babanezhad Harikandeh, Mark Schmidt, Nicolas Le Roux

ICML 2022 Towards Noise-Adaptive, Problem-Adaptive (Accelerated) Stochastic Gradient Descent Sharan Vaswani, Benjamin Dubois-Taine, Reza Babanezhad

UAI 2022 Towards Painless Policy Optimization for Constrained MDPs Arushi Jain, Sharan Vaswani, Reza Babanezhad, Csaba Szepesvári, Doina Precup

AISTATS 2021 Stochastic Polyak Step-Size for SGD: An Adaptive Learning Rate for Fast Convergence Nicolas Loizou, Sharan Vaswani, Issam Hadj Laradji, Simon Lacoste-Julien

MLJ 2020 Combining Bayesian Optimization and Lipschitz Optimization Mohamed Osama Ahmed, Sharan Vaswani, Mark Schmidt

AISTATS 2020 Fast and Furious Convergence: Stochastic Second Order Methods Under Interpolation Si Yi Meng, Sharan Vaswani, Issam Hadj Laradji), Mark Schmidt, Simon Lacoste-Julien

AISTATS 2020 Old Dog Learns New Tricks: Randomized UCB for Bandit Problems Sharan Vaswani, Abbas Mehrabian, Audrey Durand, Branislav Kveton

AISTATS 2019 Fast and Faster Convergence of SGD for Over-Parameterized Models and an Accelerated Perceptron Sharan Vaswani, Francis Bach, Mark Schmidt

ICML 2019 Garbage in, Reward Out: Bootstrapping Exploration in Multi-Armed Bandits Branislav Kveton, Csaba Szepesvari, Sharan Vaswani, Zheng Wen, Tor Lattimore, Mohammad Ghavamzadeh

NeurIPS 2019 Painless Stochastic Gradient: Interpolation, Line-Search, and Convergence Rates Sharan Vaswani, Aaron Mishkin, Issam Laradji, Mark Schmidt, Gauthier Gidel, Simon Lacoste-Julien

AISTATS 2017 Horde of Bandits Using Gaussian Markov Random Fields Sharan Vaswani, Mark Schmidt, Laks V. S. Lakshmanan

ICML 2017 Model-Independent Online Learning for Influence Maximization Sharan Vaswani, Branislav Kveton, Zheng Wen, Mohammad Ghavamzadeh, Laks V. S. Lakshmanan, Mark Schmidt

NeurIPS 2017 Online Influence Maximization Under Independent Cascade Model with Semi-Bandit Feedback Zheng Wen, Branislav Kveton, Michal Valko, Sharan Vaswani