Sridharan, Karthik

71 publications

NeurIPS 2025 Efficiently Escaping Saddle Points Under Generalized Smoothness via Self-Bounding Regularity Daniel Yiming Cao, August Y Chen, Karthik Sridharan, Benjamin Tang

ICML 2025 Online Learning with Unknown Constraints Karthik Sridharan, Seung Won Wilson Yoo

COLT 2025 Optimization, Isoperimetric Inequalities, and Sampling via Lyapunov Potentials August Y Chen, Karthik Sridharan

ICML 2025 System-Aware Unlearning Algorithms: Use Lesser, Forget Faster Linda Lu, Ayush Sekhari, Karthik Sridharan

NeurIPSW 2024 Langevin Dynamics: A Unified Perspective on Optimization via Lyapunov Potentials August Y Chen, Ayush Sekhari, Karthik Sridharan

NeurIPS 2023 Contextual Bandits and Imitation Learning with Preference-Based Active Queries Ayush Sekhari, Karthik Sridharan, Wen Sun, Runzhe Wu

ICMLW 2023 Contextual Bandits and Imitation Learning with Preference-Based Active Queries Ayush Sekhari, Karthik Sridharan, Wen Sun, Runzhe Wu

ICMLW 2023 Contextual Bandits and Imitation Learning with Preference-Based Active Queries Ayush Sekhari, Karthik Sridharan, Wen Sun, Runzhe Wu

NeurIPS 2023 Selective Sampling and Imitation Learning via Online Regression Ayush Sekhari, Karthik Sridharan, Wen Sun, Runzhe Wu

ICMLW 2023 Selective Sampling and Imitation Learning via Online Regression Ayush Sekhari, Karthik Sridharan, Wen Sun, Runzhe Wu

NeurIPS 2022 From Gradient Flow on Population Loss to Learning with Stochastic Gradient Descent Christopher M De Sa, Satyen Kale, Jason Lee, Ayush Sekhari, Karthik Sridharan

ICML 2022 Guarantees for Epsilon-Greedy Reinforcement Learning with Function Approximation Chris Dann, Yishay Mansour, Mehryar Mohri, Ayush Sekhari, Karthik Sridharan

NeurIPS 2022 On the Complexity of Adversarial Decision Making Dylan J Foster, Alexander Rakhlin, Ayush Sekhari, Karthik Sridharan

NeurIPS 2021 Agnostic Reinforcement Learning with Low-Rank MDPs and Rich Observations Ayush Sekhari, Christoph Dann, Mehryar Mohri, Yishay Mansour, Karthik Sridharan

NeurIPS 2021 SGD: The Role of Implicit Regularization, Batch-Size and Multiple-Epochs Ayush Sekhari, Karthik Sridharan, Satyen Kale

NeurIPS 2020 Online Learning with Dynamics: A Minimax Perspective Kush Bhatia, Karthik Sridharan

NeurIPS 2020 Reinforcement Learning with Feedback Graphs Christoph Dann, Yishay Mansour, Mehryar Mohri, Ayush Sekhari, Karthik Sridharan

COLT 2020 Second-Order Information in Non-Convex Stochastic Optimization: Power and Limitations Yossi Arjevani, Yair Carmon, John C. Duchi, Dylan J. Foster, Ayush Sekhari, Karthik Sridharan

ICML 2019 Distributed Learning with Sublinear Communication Jayadev Acharya, Chris De Sa, Dylan Foster, Karthik Sridharan

NeurIPS 2019 Hypothesis Set Stability and Generalization Dylan J Foster, Spencer Greenberg, Satyen Kale, Haipeng Luo, Mehryar Mohri, Karthik Sridharan

JMLR 2019 Optimization with Non-Differentiable Constraints with Applications to Fairness, Recall, Churn, and Other Goals Andrew Cotter, Heinrich Jiang, Maya Gupta, Serena Wang, Taman Narayan, Seungil You, Karthik Sridharan

COLT 2019 The Complexity of Making the Gradient Small in Stochastic Convex Optimization Dylan J. Foster, Ayush Sekhari, Ohad Shamir, Nathan Srebro, Karthik Sridharan, Blake Woodworth

ICML 2019 Training Well-Generalizing Classifiers for Fairness Metrics and Other Data-Dependent Constraints Andrew Cotter, Maya Gupta, Heinrich Jiang, Nathan Srebro, Karthik Sridharan, Serena Wang, Blake Woodworth, Seungil You

ALT 2019 Two-Player Games for Efficient Non-Convex Constrained Optimization Andrew Cotter, Heinrich Jiang, Karthik Sridharan

ALT 2018 Algorithmic Learning Theory ALT 2018: Preface Mehryar Mohri, Karthik Sridharan

AISTATS 2018 Inference in Sparse Graphs with Pairwise Measurements and Side Information Dylan J. Foster, Karthik Sridharan, Daniel Reichman

COLT 2018 Logistic Regression: The Importance of Being Improper Dylan J. Foster, Satyen Kale, Haipeng Luo, Mehryar Mohri, Karthik Sridharan

COLT 2018 Online Learning: Sufficient Statistics and the Burkholder Method Dylan J. Foster, Alexander Rakhlin, Karthik Sridharan

COLT 2018 Small-Loss Bounds for Online Learning with Partial Information Thodoris Lykouris, Karthik Sridharan, Éva Tardos

NeurIPS 2018 Uniform Convergence of Gradients for Non-Convex Learning and Optimization Dylan J Foster, Ayush Sekhari, Karthik Sridharan

AISTATS 2017 Efficient Online Multiclass Prediction on Graphs via Surrogate Losses Alexander Rakhlin, Karthik Sridharan

COLT 2017 On Equivalence of Martingale Tail Bounds and Deterministic Regret Inequalities Alexander Rakhlin, Karthik Sridharan

NeurIPS 2017 Parameter-Free Online Learning via Model Selection Dylan J Foster, Satyen Kale, Mehryar Mohri, Karthik Sridharan

COLT 2017 ZigZag: A New Approach to Adaptive Online Learning Dylan J. Foster, Alexander Rakhlin, Karthik Sridharan

ICML 2016 BISTRO: An Efficient Relaxation-Based Method for Contextual Bandits Alexander Rakhlin, Karthik Sridharan

NeurIPS 2016 Exploiting the Structure: Stochastic Gradient Methods Using Raw Clusters Zeyuan Allen-Zhu, Yang Yuan, Karthik Sridharan

NeurIPS 2016 Learning in Games: Robustness of Fast Convergence Dylan J Foster, Zhiyuan Li, Thodoris Lykouris, Karthik Sridharan, Eva Tardos

AISTATS 2016 Private Causal Inference Matt J. Kusner, Yu Sun, Karthik Sridharan, Kilian Q. Weinberger

NeurIPS 2015 Adaptive Online Learning Dylan J Foster, Alexander Rakhlin, Karthik Sridharan

COLT 2015 Hierarchies of Relaxations for Online Prediction Problems with Evolving Constraints Alexander Rakhlin, Karthik Sridharan

COLT 2015 Learning with Square Loss: Localization Through Offset Rademacher Complexity Tengyuan Liang, Alexander Rakhlin, Karthik Sridharan

JMLR 2015 Online Learning via Sequential Complexities Alexander Rakhlin, Karthik Sridharan, Ambuj Tewari

AISTATS 2015 Online Optimization : Competing with Dynamic Comparators Ali Jadbabaie, Alexander Rakhlin, Shahin Shahrampour, Karthik Sridharan

COLT 2014 Online Non-Parametric Regression Alexander Rakhlin, Karthik Sridharan

COLT 2013 Competing with Strategies Wei Han, Alexander Rakhlin, Karthik Sridharan

AISTATS 2013 Localization and Adaptation in Online Learning Alexander Rakhlin, Ohad Shamir, Karthik Sridharan

COLT 2013 Online Learning with Predictable Sequences Alexander Rakhlin, Karthik Sridharan

NeurIPS 2013 Optimization, Learning, and Games with Predictable Sequences Sasha Rakhlin, Karthik Sridharan

ICML 2012 Making Gradient Descent Optimal for Strongly Convex Stochastic Optimization Alexander Rakhlin, Ohad Shamir, Karthik Sridharan

ICML 2012 Minimizing the Misclassification Error Rate Using a Surrogate Convex Loss Shai Ben-David, David Loker, Nathan Srebro, Karthik Sridharan

NeurIPS 2012 Relax and Randomize : From Value to Algorithms Sasha Rakhlin, Ohad Shamir, Karthik Sridharan

JMLR 2012 Selective Sampling and Active Learning from Single and Multiple Teachers Ofer Dekel, Claudio Gentile, Karthik Sridharan

NeurIPS 2011 Better Mini-Batch Algorithms via Accelerated Gradient Methods Andrew Cotter, Ohad Shamir, Nati Srebro, Karthik Sridharan

COLT 2011 Complexity-Based Approach to Calibration with Checking Rules Dean P. Foster, Alexander Rakhlin, Karthik Sridharan, Ambuj Tewari

IJCAI 2011 Learning Linear and Kernel Predictors with the 0-1 Loss Function Shai Shalev-Shwartz, Ohad Shamir, Karthik Sridharan

NeurIPS 2011 On the Universality of Online Mirror Descent Nati Srebro, Karthik Sridharan, Ambuj Tewari

COLT 2011 Online Learning: Beyond Regret Alexander Rakhlin, Karthik Sridharan, Ambuj Tewari

NeurIPS 2011 Online Learning: Stochastic, Constrained, and Smoothed Adversaries Alexander Rakhlin, Karthik Sridharan, Ambuj Tewari

COLT 2010 Convex Games in Banach Spaces Karthik Sridharan, Ambuj Tewari

JMLR 2010 Learnability, Stability and Uniform Convergence Shai Shalev-Shwartz, Ohad Shamir, Nathan Srebro, Karthik Sridharan

COLT 2010 Learning Kernel-Based Halfspaces with the Zero-One Loss Shai Shalev-Shwartz, Ohad Shamir, Karthik Sridharan

NeurIPS 2010 Online Learning: Random Averages, Combinatorial Parameters, and Learnability Alexander Rakhlin, Karthik Sridharan, Ambuj Tewari

COLT 2010 Robust Selective Sampling from Single and Multiple Teachers Ofer Dekel, Claudio Gentile, Karthik Sridharan

NeurIPS 2010 Smoothness, Low Noise and Fast Rates Nathan Srebro, Karthik Sridharan, Ambuj Tewari

COLT 2009 Learnability and Stability in the General Learning Setting Shai Shalev-Shwartz, Ohad Shamir, Nathan Srebro, Karthik Sridharan

ICML 2009 Multi-View Clustering via Canonical Correlation Analysis Kamalika Chaudhuri, Sham M. Kakade, Karen Livescu, Karthik Sridharan

COLT 2009 Stochastic Convex Optimization Shai Shalev-Shwartz, Ohad Shamir, Nathan Srebro, Karthik Sridharan

COLT 2009 The Complexity of Improperly Learning Large Margin Halfspaces Shai Shalev-Shwartz, Ohad Shamir, Karthik Sridharan

COLT 2008 An Information Theoretic Framework for Multi-View Learning Karthik Sridharan, Sham M. Kakade

NeurIPS 2008 Fast Rates for Regularized Objectives Karthik Sridharan, Shai Shalev-shwartz, Nathan Srebro

NeurIPS 2008 On the Complexity of Linear Prediction: Risk Bounds, Margin Bounds, and Regularization Sham M. Kakade, Karthik Sridharan, Ambuj Tewari