Sharan Vaswani

According to our database, Sharan Vaswani authored at least 32 papers between 2013 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

From Inverse Optimization to Feasibility to ERM.

Saurabh Mishra, Anant Raj, Sharan Vaswani

CoRR, 2024

Noise-adaptive (Accelerated) Stochastic Heavy-Ball Momentum.

Anh Dang, Reza Babanezhad, Sharan Vaswani

CoRR, 2024

2023

Decision-Aware Actor-Critic with Function Approximation and Theoretical Guarantees.

Sharan Vaswani, Amirreza Kazemi, Reza Babanezhad Harikandeh, Nicolas Le Roux

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Target-based Surrogates for Stochastic Optimization.

Jonathan Wilder Lavington, Sharan Vaswani, Reza Babanezhad Harikandeh, Mark Schmidt, Nicolas Le Roux

Proceedings of the International Conference on Machine Learning, 2023

2022

SVRG meets AdaGrad: painless variance reduction.

Benjamin Dubois-Taine, Sharan Vaswani, Reza Babanezhad, Mark Schmidt, Simon Lacoste-Julien

Mach. Learn., 2022

Towards Painless Policy Optimization for Constrained MDPs.

Arushi Jain, Sharan Vaswani, Reza Babanezhad, Csaba Szepesvári, Doina Precup

CoRR, 2022

Towards painless policy optimization for constrained MDPs.

Arushi Jain, Sharan Vaswani, Reza Babanezhad, Csaba Szepesváari, Doina Precup

Proceedings of the Uncertainty in Artificial Intelligence, 2022

Near-Optimal Sample Complexity Bounds for Constrained MDPs.

Sharan Vaswani, Lin Yang, Csaba Szepesvári

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Towards Noise-adaptive, Problem-adaptive (Accelerated) Stochastic Gradient Descent.

Sharan Vaswani, Benjamin Dubois-Taine, Reza Babanezhad

Proceedings of the International Conference on Machine Learning, 2022

Improved Policy Optimization for Online Imitation Learning.

Jonathan Wilder Lavington, Sharan Vaswani, Mark Schmidt

Proceedings of the Conference on Lifelong Learning Agents, 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

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Towards Noise-adaptive, Problem-adaptive Stochastic Gradient Descent.

Sharan Vaswani, Benjamin Dubois-Taine, Reza Babanezhad

CoRR, 2021

A functional mirror ascent view of policy gradient methods with function approximation.

Sharan Vaswani, Olivier Bachem, Simone Totaro, Robert Mueller, Matthieu Geist, Marlos C. Machado, Pablo Samuel Castro, Nicolas Le Roux

CoRR, 2021

Stochastic Polyak Step-size for SGD: An Adaptive Learning Rate for Fast Convergence.

Nicolas Loizou, Sharan Vaswani, Issam Hadj Laradji, Simon Lacoste-Julien

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Combining Bayesian optimization and Lipschitz optimization.

Mohamed Osama Ahmed, Sharan Vaswani, Mark Schmidt

Mach. Learn., 2020

Adaptive Gradient Methods Converge Faster with Over-Parameterization (and you can do a line-search).

Sharan Vaswani, Frederik Kunstner, Issam H. Laradji, Si Yi Meng, Mark Schmidt, Simon Lacoste-Julien

CoRR, 2020

To Each Optimizer a Norm, To Each Norm its Generalization.

Sharan Vaswani, Reza Babanezhad, Jose Gallego, Aaron Mishkin, Simon Lacoste-Julien, Nicolas Le Roux

CoRR, 2020

Old Dog Learns New Tricks: Randomized UCB for Bandit Problems.

Sharan Vaswani, Abbas Mehrabian, Audrey Durand, Branislav Kveton

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Fast and Furious Convergence: Stochastic Second Order Methods under Interpolation.

Si Yi Meng, Sharan Vaswani, Issam Hadj Laradji, Mark Schmidt, Simon Lacoste-Julien

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Painless Stochastic Gradient: Interpolation, Line-Search, and Convergence Rates.

Sharan Vaswani, Aaron Mishkin, Issam H. Laradji, Mark Schmidt, Gauthier Gidel, Simon Lacoste-Julien

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Garbage In, Reward Out: Bootstrapping Exploration in Multi-Armed Bandits.

Branislav Kveton, Csaba Szepesvári, Sharan Vaswani, Zheng Wen, Tor Lattimore, Mohammad Ghavamzadeh

Proceedings of the 36th International Conference on Machine Learning, 2019

Fast and Faster Convergence of SGD for Over-Parameterized Models and an Accelerated Perceptron.

Sharan Vaswani, Francis R. Bach, Mark Schmidt

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

New Insights into Bootstrapping for Bandits.

Sharan Vaswani, Branislav Kveton, Zheng Wen, Anup Rao, Mark Schmidt, Yasin Abbasi-Yadkori

CoRR, 2018

2017

Diffusion Independent Semi-Bandit Influence Maximization.

Sharan Vaswani, Branislav Kveton, Zheng Wen, Mohammad Ghavamzadeh, Laks V. S. Lakshmanan, Mark Schmidt

CoRR, 2017

Online Influence Maximization under Independent Cascade Model with Semi-Bandit Feedback.

Zheng Wen, Branislav Kveton, Michal Valko, Sharan Vaswani

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Model-Independent Online Learning for Influence Maximization.

Sharan Vaswani, Branislav Kveton, Zheng Wen, Mohammad Ghavamzadeh, Laks V. S. Lakshmanan, Mark Schmidt

Proceedings of the 34th International Conference on Machine Learning, 2017

Horde of Bandits using Gaussian Markov Random Fields.

Sharan Vaswani, Mark Schmidt, Laks V. S. Lakshmanan

Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016

Adaptive Influence Maximization in Social Networks: Why Commit when You can Adapt?

Sharan Vaswani, Laks V. S. Lakshmanan

CoRR, 2016

2015

Influence Maximization with Bandits.

Sharan Vaswani, Laks V. S. Lakshmanan

CoRR, 2015

2014

Modeling non-progressive phenomena for influence propagation.

Vincent Yun Lou, Smriti Bhagat, Laks V. S. Lakshmanan, Sharan Vaswani

Proceedings of the second ACM conference on Online social networks, 2014

2013

Fast 3D Salient Region Detection in Medical Images using GPUs.

Rahul Thota, Sharan Vaswani, Amit A. Kale, Nagavijayalakshmi Vydyanathan

CoRR, 2013

Performance evaluation of medical imaging algorithms on Intel^® MIC platform.

Jyotsna Khemka, Mrugesh R. Gajjar, Sharan Vaswani, Naga Vydyanathan, Rama Malladi, Vinutha S. V

Proceedings of the 20th Annual International Conference on High Performance Computing, 2013