Performance evaluation of medical imaging algorithms on Intel® MIC platform. - Jyotsna Khemka; Mrugesh R. Gajjar; Sharan Vaswani; Naga Vydyanathan; Rama Malladi; Vinutha S. V (HiPC, 2013)

Fast 3D Salient Region Detection in Medical Images using GPUs. - Rahul Thota; Sharan Vaswani; Amit A. Kale; Nagavijayalakshmi Vydyanathan (CoRR, 2013)

Modeling non-progressive phenomena for influence propagation. - Vincent Yun Lou; Smriti Bhagat; Laks V. S. Lakshmanan; Sharan Vaswani (COSN, 2014)

Influence Maximization with Bandits. - Sharan Vaswani; Laks V. S. Lakshmanan (CoRR, 2015)

Adaptive Influence Maximization in Social Networks: Why Commit when You can Adapt? - Sharan Vaswani; Laks V. S. Lakshmanan (CoRR, 2016)

Horde of Bandits using Gaussian Markov Random Fields. - Sharan Vaswani; Mark Schmidt 001; Laks V. S. Lakshmanan (AISTATS, 2017)

Model-Independent Online Learning for Influence Maximization. - Sharan Vaswani; Branislav Kveton; Zheng Wen 002; Mohammad Ghavamzadeh; Laks V. S. Lakshmanan; Mark Schmidt 001 (ICML, 2017)

Online Influence Maximization under Independent Cascade Model with Semi-Bandit Feedback. - Zheng Wen; Branislav Kveton; Michal Valko; Sharan Vaswani (NIPS, 2017)

Diffusion Independent Semi-Bandit Influence Maximization. - Sharan Vaswani; Branislav Kveton; Zheng Wen 002; Mohammad Ghavamzadeh; Laks V. S. Lakshmanan; Mark Schmidt 001 (CoRR, 2017)

New Insights into Bootstrapping for Bandits. - Sharan Vaswani; Branislav Kveton; Zheng Wen 002; Anup Rao 002; Mark Schmidt 001; Yasin Abbasi-Yadkori (CoRR, 2018)

Fast and Faster Convergence of SGD for Over-Parameterized Models and an Accelerated Perceptron. - Sharan Vaswani; Francis R. Bach; Mark Schmidt 001 (AISTATS, 2019)

Garbage In, Reward Out: Bootstrapping Exploration in Multi-Armed Bandits. - Branislav Kveton; Csaba Szepesvári; Sharan Vaswani; Zheng Wen 002; Tor Lattimore; Mohammad Ghavamzadeh (ICML, 2019)

Painless Stochastic Gradient: Interpolation, Line-Search, and Convergence Rates. - Sharan Vaswani; Aaron Mishkin; Issam H. Laradji; Mark Schmidt 001; Gauthier Gidel; Simon Lacoste-Julien (NeurIPS, 2019)

Fast and Furious Convergence: Stochastic Second Order Methods under Interpolation. - Si Yi Meng; Sharan Vaswani; Issam Hadj Laradji; Mark Schmidt 001; Simon Lacoste-Julien (AISTATS, 2020)

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

To Each Optimizer a Norm, To Each Norm its Generalization. - Sharan Vaswani; Reza Babanezhad 001; Jose Gallego; Aaron Mishkin; Simon Lacoste-Julien; Nicolas Le Roux (CoRR, 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 001; Simon Lacoste-Julien (CoRR, 2020)

Combining Bayesian optimization and Lipschitz optimization. - Mohamed Osama Ahmed; Sharan Vaswani; Mark Schmidt 001 (Mach. Learn., 2020)

Stochastic Polyak Step-size for SGD: An Adaptive Learning Rate for Fast Convergence. - Nicolas Loizou; Sharan Vaswani; Issam Hadj Laradji; Simon Lacoste-Julien (AISTATS, 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)

Towards Noise-adaptive, Problem-adaptive Stochastic Gradient Descent. - Sharan Vaswani; Benjamin Dubois-Taine; Reza Babanezhad 001 (CoRR, 2021)

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 (AISTATS, 2022)

Improved Policy Optimization for Online Imitation Learning. - Jonathan Wilder Lavington; Sharan Vaswani; Mark Schmidt 001 (CoLLAs, 2022)

Towards Noise-adaptive, Problem-adaptive (Accelerated) Stochastic Gradient Descent. - Sharan Vaswani; Benjamin Dubois-Taine; Reza Babanezhad 001 (ICML, 2022)

Near-Optimal Sample Complexity Bounds for Constrained MDPs. - Sharan Vaswani; Lin Yang 011; Csaba Szepesvári (NeurIPS, 2022)

Towards painless policy optimization for constrained MDPs. - Arushi Jain; Sharan Vaswani; Reza Babanezhad 001; Csaba Szepesváari; Doina Precup (UAI, 2022)

Towards Painless Policy Optimization for Constrained MDPs. - Arushi Jain; Sharan Vaswani; Reza Babanezhad 001; Csaba Szepesvári; Doina Precup (CoRR, 2022)

SVRG meets AdaGrad: painless variance reduction. - Benjamin Dubois-Taine; Sharan Vaswani; Reza Babanezhad 001; Mark Schmidt 001; Simon Lacoste-Julien (Mach. Learn., 2022)

Target-based Surrogates for Stochastic Optimization. - Jonathan Wilder Lavington; Sharan Vaswani; Reza Babanezhad Harikandeh; Mark Schmidt 001; Nicolas Le Roux (ICML, 2023)

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

From Inverse Optimization to Feasibility to ERM. - Saurabh Mishra; Anant Raj; Sharan Vaswani (ICML, 2024)

Small steps no more: Global convergence of stochastic gradient bandits for arbitrary learning rates. - Jincheng Mei; Bo Dai 001; Alekh Agarwal; Sharan Vaswani; Anant Raj; Csaba Szepesvári; Dale Schuurmans (NeurIPS, 2024)

Towards Principled, Practical Policy Gradient for Bandits and Tabular MDPs. - Michael Lu; Matin Aghaei; Anant Raj; Sharan Vaswani (RLJ, 2024)

Noise-adaptive (Accelerated) Stochastic Heavy-Ball Momentum. - Anh Quang Dang; Reza Babanezhad 001; Sharan Vaswani (CoRR, 2024)

Improving OOD Generalization of Pre-trained Encoders via Aligned Embedding-Space Ensembles. - Shuman Peng; Arash Khoeini; Sharan Vaswani; Martin Ester (CoRR, 2024)

Fast Convergence of Softmax Policy Mirror Ascent. - Reza Asad; Reza Babanezhad Harikandeh; Issam H. Laradji; Nicolas Le Roux; Sharan Vaswani (AISTATS, 2025)

(Accelerated) Noise-adaptive Stochastic Heavy-Ball Momentum. - Anh Quang Dang; Reza Babanezhad Harikandeh; Sharan Vaswani (Trans. Mach. Learn. Res., 2025)

Armijo Line-search Makes (Stochastic) Gradient Descent Go Fast. - Sharan Vaswani; Reza Babanezhad 001 (CoRR, 2025)

Rethinking the Global Convergence of Softmax Policy Gradient with Linear Function Approximation. - Max Qiushi Lin; Jincheng Mei; Matin Aghaei; Michael Lu; Bo Dai 001; Alekh Agarwal; Dale Schuurmans; Csaba Szepesvári; Sharan Vaswani (CoRR, 2025)

Preserving Plasticity in Continual Learning with Adaptive Linearity Injection. - Seyed Roozbeh Razavi Rohani; Khashayar Khajavi; Wesley Chung; Mo Chen; Sharan Vaswani (CoRR, 2025)

Glocal Smoothness: Line Search can really help! - Curtis Fox; Aaron Mishkin; Sharan Vaswani; Mark Schmidt 001 (CoRR, 2025)

Sample Complexity Bounds for Linear Constrained MDPs with a Generative Model. - Xingtu Liu 001; Lin F. Yang; Sharan Vaswani (CoRR, 2025)

Revisiting Actor-Critic Methods in Discrete Action Off-Policy Reinforcement Learning. - Reza Asad; Reza Babanezhad 001; Sharan Vaswani (CoRR, 2025)