Karthik Sridharan

131 papers A* 42A 5B 3C 1Journal 63Unranked 17

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	On the Robustness of Langevin Dynamics to Score Function Error. CoRR Daniel Yiming Cao, August Y. Chen, Karthik Sridharan, Yuchen Wu
2025	J	`jnl`	Active Learning via Regression Beyond Realizability. CoRR Atul Ganju, Shashaank Aiyer, Ved Sriraman, Karthik Sridharan
2025	J	`jnl`	Efficiently Escaping Saddle Points under Generalized Smoothness via Self-Bounding Regularity. CoRR Daniel Yiming Cao, August Y. Chen, Karthik Sridharan, Benjamin Tang
2025	A*	`conf`	Online Learning with Unknown Constraints. ICML Karthik Sridharan, Seung Won Wilson Yoo
2025	A*	`conf`	Optimization, Isoperimetric Inequalities, and Sampling via Lyapunov Potentials. COLT August Y. Chen, Karthik Sridharan
2025	A*	`conf`	System-Aware Unlearning Algorithms: Use Lesser, Forget Faster. ICML Linda Lu, Ayush Sekhari, Karthik Sridharan
2025	J	`jnl`	System-Aware Unlearning Algorithms: Use Lesser, Forget Faster. CoRR Linda Lu, Ayush Sekhari, Karthik Sridharan
2024	J	`jnl`	From Optimization to Sampling via Lyapunov Potentials. CoRR August Y. Chen, Karthik Sridharan
2024	J	`jnl`	Langevin Dynamics: A Unified Perspective on Optimization via Lyapunov Potentials. CoRR August Y. Chen, Ayush Sekhari, Karthik Sridharan
2024	J	`jnl`	Online Learning with Unknown Constraints. CoRR Karthik Sridharan, Seung Won Wilson Yoo
2023	J	`jnl`	Contextual Bandits and Imitation Learning via Preference-Based Active Queries. CoRR Ayush Sekhari, Karthik Sridharan, Wen Sun, Runzhe Wu
2023	A*	`conf`	Contextual Bandits and Imitation Learning with Preference-Based Active Queries. NeurIPS Ayush Sekhari, Karthik Sridharan, Wen Sun, Runzhe Wu
2023	A*	`conf`	Selective Sampling and Imitation Learning via Online Regression. NeurIPS Ayush Sekhari, Karthik Sridharan, Wen Sun, Runzhe Wu
2023	J	`jnl`	Selective Sampling and Imitation Learning via Online Regression. CoRR Ayush Sekhari, Karthik Sridharan, Wen Sun, Runzhe Wu
2022	A*	`conf`	From Gradient Flow on Population Loss to Learning with Stochastic Gradient Descent. NeurIPS Christopher De Sa, Satyen Kale, Jason D. Lee, Ayush Sekhari, Karthik Sridharan
2022	J	`jnl`	From Gradient Flow on Population Loss to Learning with Stochastic Gradient Descent. CoRR Satyen Kale, Jason D. Lee, Chris De Sa, Ayush Sekhari, Karthik Sridharan
2022	A*	`conf`	Guarantees for Epsilon-Greedy Reinforcement Learning with Function Approximation. ICML Christoph Dann, Yishay Mansour, Mehryar Mohri, Ayush Sekhari, Karthik Sridharan
2022	J	`jnl`	Guarantees for Epsilon-Greedy Reinforcement Learning with Function Approximation. CoRR Christoph Dann, Yishay Mansour, Mehryar Mohri, Ayush Sekhari, Karthik Sridharan
2022	A*	`conf`	On the Complexity of Adversarial Decision Making. NeurIPS Dylan J. Foster, Alexander Rakhlin, Ayush Sekhari, Karthik Sridharan
2022	J	`jnl`	On the Complexity of Adversarial Decision Making. CoRR Dylan J. Foster, Alexander Rakhlin, Ayush Sekhari, Karthik Sridharan
2022	J	`jnl`	Small-Loss Bounds for Online Learning with Partial Information. Math. Oper. Res. Thodoris Lykouris, Karthik Sridharan, Éva Tardos
2021	A*	`conf`	Agnostic Reinforcement Learning with Low-Rank MDPs and Rich Observations. NeurIPS Ayush Sekhari, Christoph Dann, Mehryar Mohri, Yishay Mansour, Karthik Sridharan
2021	J	`jnl`	Agnostic Reinforcement Learning with Low-Rank MDPs and Rich Observations. CoRR Christoph Dann, Yishay Mansour, Mehryar Mohri, Ayush Sekhari, Karthik Sridharan
2021	A*	`conf`	SGD: The Role of Implicit Regularization, Batch-size and Multiple-epochs. NeurIPS Ayush Sekhari, Karthik Sridharan, Satyen Kale
2021	J	`jnl`	SGD: The Role of Implicit Regularization, Batch-size and Multiple-epochs. CoRR Satyen Kale, Ayush Sekhari, Karthik Sridharan
2020	A*	`conf`	Online learning with dynamics: A minimax perspective. NeurIPS Kush Bhatia, Karthik Sridharan
2020	J	`jnl`	Online learning with dynamics: A minimax perspective. CoRR Kush Bhatia, Karthik Sridharan
2020	A*	`conf`	Reinforcement Learning with Feedback Graphs. NeurIPS Christoph Dann, Yishay Mansour, Mehryar Mohri, Ayush Sekhari, Karthik Sridharan
2020	J	`jnl`	Reinforcement Learning with Feedback Graphs. CoRR Christoph Dann, Yishay Mansour, Mehryar Mohri, Ayush Sekhari, Karthik Sridharan
2020	A*	`conf`	Second-Order Information in Non-Convex Stochastic Optimization: Power and Limitations. COLT Yossi Arjevani, Yair Carmon, John C. Duchi, Dylan J. Foster, Ayush Sekhari, Karthik Sridharan
2020	J	`jnl`	Second-Order Information in Non-Convex Stochastic Optimization: Power and Limitations. CoRR Yossi Arjevani, Yair Carmon, John C. Duchi, Dylan J. Foster, Ayush Sekhari, Karthik Sridharan
2019	A*	`conf`	Distributed Learning with Sublinear Communication. ICML Jayadev Acharya, Chris De Sa, Dylan J. Foster, Karthik Sridharan
2019	J	`jnl`	Distributed Learning with Sublinear Communication. CoRR Jayadev Acharya, Christopher De Sa, Dylan J. Foster, Karthik Sridharan
2019	A*	`conf`	Hypothesis Set Stability and Generalization. NeurIPS Dylan J. Foster, Spencer Greenberg, Satyen Kale, Haipeng Luo, Mehryar Mohri, Karthik Sridharan
2019	J	`jnl`	Hypothesis Set Stability and Generalization. CoRR Dylan J. Foster, Spencer Greenberg, Satyen Kale, Haipeng Luo, Mehryar Mohri, Karthik Sridharan
2019	J	`jnl`	Optimization with Non-Differentiable Constraints with Applications to Fairness, Recall, Churn, and Other Goals. J. Mach. Learn. Res. Andrew Cotter, Heinrich Jiang, Maya R. Gupta, Serena Lutong Wang, Taman Narayan, Seungil You, Karthik Sridharan
2019	A*	`conf`	The Complexity of Making the Gradient Small in Stochastic Convex Optimization. COLT Dylan J. Foster, Ayush Sekhari, Ohad Shamir, Nathan Srebro, Karthik Sridharan, Blake E. Woodworth
2019	J	`jnl`	The Complexity of Making the Gradient Small in Stochastic Convex Optimization. CoRR Dylan J. Foster, Ayush Sekhari, Ohad Shamir, Nathan Srebro, Karthik Sridharan, Blake E. Woodworth
2019	A*	`conf`	Training Well-Generalizing Classifiers for Fairness Metrics and Other Data-Dependent Constraints. ICML Andrew Cotter, Maya R. Gupta, Heinrich Jiang, Nathan Srebro, Karthik Sridharan, Serena Lutong Wang, Blake E. Woodworth, Seungil You
2019	B	`conf`	Two-Player Games for Efficient Non-Convex Constrained Optimization. ALT Andrew Cotter, Heinrich Jiang, Karthik Sridharan
2018	B	`ed.`	Algorithmic Learning Theory, ALT 2018, 7-9 April 2018, Lanzarote, Canary Islands, Spain ALT Firdaus Janoos, Mehryar Mohri, Karthik Sridharan
2018	A	`conf`	Inference in Sparse Graphs with Pairwise Measurements and Side Information. AISTATS Dylan J. Foster, Karthik Sridharan, Daniel Reichman
2018	A*	`conf`	Logistic Regression: The Importance of Being Improper. COLT Dylan J. Foster, Satyen Kale, Haipeng Luo, Mehryar Mohri, Karthik Sridharan
2018	J	`jnl`	Logistic Regression: The Importance of Being Improper. CoRR Dylan J. Foster, Satyen Kale, Haipeng Luo, Mehryar Mohri, Karthik Sridharan
2018	A*	`conf`	Online Learning: Sufficient Statistics and the Burkholder Method. COLT Dylan J. Foster, Alexander Rakhlin, Karthik Sridharan
2018	J	`jnl`	Online Learning: Sufficient Statistics and the Burkholder Method. CoRR Dylan J. Foster, Alexander Rakhlin, Karthik Sridharan
2018	J	`jnl`	Optimization with Non-Differentiable Constraints with Applications to Fairness, Recall, Churn, and Other Goals. CoRR Andrew Cotter, Heinrich Jiang, Serena Lutong Wang, Taman Narayan, Maya R. Gupta, Seungil You, Karthik Sridharan
2018	J	`jnl`	Parameter-free online learning via model selection. CoRR Dylan J. Foster, Satyen Kale, Mehryar Mohri, Karthik Sridharan
2018	A*	`conf`	Small-loss bounds for online learning with partial information. COLT Thodoris Lykouris, Karthik Sridharan, Éva Tardos
2018	J	`jnl`	Training Well-Generalizing Classifiers for Fairness Metrics and Other Data-Dependent Constraints. CoRR Andrew Cotter, Maya R. Gupta, Heinrich Jiang, Nathan Srebro, Karthik Sridharan, Serena Lutong Wang, Blake E. Woodworth, Seungil You
2018	J	`jnl`	Two-Player Games for Efficient Non-Convex Constrained Optimization. CoRR Andrew Cotter, Heinrich Jiang, Karthik Sridharan
2018	A*	`conf`	Uniform Convergence of Gradients for Non-Convex Learning and Optimization. NeurIPS Dylan J. Foster, Ayush Sekhari, Karthik Sridharan
2018	J	`jnl`	Uniform Convergence of Gradients for Non-Convex Learning and Optimization. CoRR Dylan J. Foster, Ayush Sekhari, Karthik Sridharan
2017	A	`conf`	Efficient Online Multiclass Prediction on Graphs via Surrogate Losses. AISTATS Alexander Rakhlin, Karthik Sridharan
2017	J	`jnl`	Inference in Sparse Graphs with Pairwise Measurements and Side Information. CoRR Dylan J. Foster, Daniel Reichman, Karthik Sridharan
2017	A*	`conf`	On Equivalence of Martingale Tail Bounds and Deterministic Regret Inequalities. COLT Alexander Rakhlin, Karthik Sridharan
2017	—	`conf`	Parameter-Free Online Learning via Model Selection. NIPS Dylan J. Foster, Satyen Kale, Mehryar Mohri, Karthik Sridharan
2017	J	`jnl`	Small-loss bounds for online learning with partial information. CoRR Thodoris Lykouris, Karthik Sridharan, Éva Tardos
2017	A*	`conf`	ZigZag: A New Approach to Adaptive Online Learning. COLT Dylan J. Foster, Alexander Rakhlin, Karthik Sridharan
2017	J	`jnl`	ZigZag: A new approach to adaptive online learning. CoRR Dylan J. Foster, Alexander Rakhlin, Karthik Sridharan
2016	J	`jnl`	A Tutorial on Online Supervised Learning with Applications to Node Classification in Social Networks. CoRR Alexander Rakhlin, Karthik Sridharan
2016	A*	`conf`	BISTRO: An Efficient Relaxation-Based Method for Contextual Bandits. ICML Alexander Rakhlin, Karthik Sridharan
2016	J	`jnl`	BISTRO: An Efficient Relaxation-Based Method for Contextual Bandits. CoRR Alexander Rakhlin, Karthik Sridharan
2016	—	`conf`	Exploiting the Structure: Stochastic Gradient Methods Using Raw Clusters. NIPS Zeyuan Allen Zhu, Yang Yuan, Karthik Sridharan
2016	J	`jnl`	Exploiting the Structure: Stochastic Gradient Methods Using Raw Clusters. CoRR Zeyuan Allen Zhu, Yang Yuan, Karthik Sridharan
2016	J	`jnl`	Fast Convergence of Common Learning Algorithms in Games. CoRR Dylan J. Foster, Zhiyuan Li, Thodoris Lykouris, Karthik Sridharan, Éva Tardos
2016	—	`conf`	Learning in Games: Robustness of Fast Convergence. NIPS Dylan J. Foster, Zhiyuan Li, Thodoris Lykouris, Karthik Sridharan, Éva Tardos
2016	A	`conf`	Private Causal Inference. AISTATS Matt J. Kusner, Yu Sun, Karthik Sridharan, Kilian Q. Weinberger
2015	—	`conf`	Adaptive Online Learning. NIPS Dylan J. Foster, Alexander Rakhlin, Karthik Sridharan
2015	J	`jnl`	Adaptive Online Learning. CoRR Dylan J. Foster, Alexander Rakhlin, Karthik Sridharan
2015	A*	`conf`	Hierarchies of Relaxations for Online Prediction Problems with Evolving Constraints. COLT Alexander Rakhlin, Karthik Sridharan
2015	J	`jnl`	Hierarchies of Relaxations for Online Prediction Problems with Evolving Constraints. CoRR Alexander Rakhlin, Karthik Sridharan
2015	A*	`conf`	Learning with Square Loss: Localization through Offset Rademacher Complexity. COLT Tengyuan Liang, Alexander Rakhlin, Karthik Sridharan
2015	J	`jnl`	Learning with Square Loss: Localization through Offset Rademacher Complexity. CoRR Tengyuan Liang, Alexander Rakhlin, Karthik Sridharan
2015	J	`jnl`	On Equivalence of Martingale Tail Bounds and Deterministic Regret Inequalities. CoRR Alexander Rakhlin, Karthik Sridharan
2015	J	`jnl`	Online Nonparametric Regression with General Loss Functions. CoRR Alexander Rakhlin, Karthik Sridharan
2015	A	`conf`	Online Optimization : Competing with Dynamic Comparators. AISTATS Ali Jadbabaie, Alexander Rakhlin, Shahin Shahrampour, Karthik Sridharan
2015	J	`jnl`	Online Optimization : Competing with Dynamic Comparators. CoRR Ali Jadbabaie, Alexander Rakhlin, Shahin Shahrampour, Karthik Sridharan
2015	J	`jnl`	Online learning via sequential complexities. J. Mach. Learn. Res. Alexander Rakhlin, Karthik Sridharan, Ambuj Tewari
2015	J	`jnl`	Sequential Probability Assignment with Binary Alphabets and Large Classes of Experts. CoRR Alexander Rakhlin, Karthik Sridharan
2014	A*	`conf`	Online Non-Parametric Regression. COLT Alexander Rakhlin, Karthik Sridharan
2014	J	`jnl`	Online Nonparametric Regression. CoRR Alexander Rakhlin, Karthik Sridharan
2013	J	`jnl`	Competing With Strategies CoRR Wei Han, Alexander Rakhlin, Karthik Sridharan
2013	A*	`conf`	Competing With Strategies. COLT Wei Han, Alexander Rakhlin, Karthik Sridharan
2013	J	`jnl`	Empirical Entropy, Minimax Regret and Minimax Risk. CoRR Alexander Rakhlin, Karthik Sridharan, Alexandre B. Tsybakov
2013	A	`conf`	Localization and Adaptation in Online Learning. AISTATS Alexander Rakhlin, Ohad Shamir, Karthik Sridharan
2013	B	`conf`	On Semi-Probabilistic universal prediction. ITW Alexander Rakhlin, Karthik Sridharan
2013	A*	`conf`	Online Learning with Predictable Sequences. COLT Alexander Rakhlin, Karthik Sridharan
2013	—	`conf`	Optimization, Learning, and Games with Predictable Sequences. NIPS Alexander Rakhlin, Karthik Sridharan
2013	J	`jnl`	Optimization, Learning, and Games with Predictable Sequences. CoRR Alexander Rakhlin, Karthik Sridharan
2012	J	`jnl`	Learning From An Optimization Viewpoint CoRR Karthik Sridharan
2012	A*	`conf`	Making Gradient Descent Optimal for Strongly Convex Stochastic Optimization. ICML Alexander Rakhlin, Ohad Shamir, Karthik Sridharan
2012	A*	`conf`	Minimizing The Misclassification Error Rate Using a Surrogate Convex Loss. ICML Shai Ben-David, David Loker, Nathan Srebro, Karthik Sridharan
2012	J	`jnl`	Online Learning with Predictable Sequences CoRR Alexander Rakhlin, Karthik Sridharan
2012	J	`jnl`	Relax and Localize: From Value to Algorithms CoRR Alexander Rakhlin, Ohad Shamir, Karthik Sridharan
2012	—	`conf`	Relax and Randomize : From Value to Algorithms. NIPS Alexander Rakhlin, Ohad Shamir, Karthik Sridharan
2012	J	`jnl`	Selective sampling and active learning from single and multiple teachers. J. Mach. Learn. Res. Ofer Dekel, Claudio Gentile, Karthik Sridharan
2011	J	`jnl`	Better Mini-Batch Algorithms via Accelerated Gradient Methods CoRR Andrew Cotter, Ohad Shamir, Nathan Srebro, Karthik Sridharan
2011	—	`conf`	Better Mini-Batch Algorithms via Accelerated Gradient Methods. NIPS Andrew Cotter, Ohad Shamir, Nati Srebro, Karthik Sridharan
2011	A*	`conf`	Complexity-Based Approach to Calibration with Checking Rules. COLT Dean P. Foster, Alexander Rakhlin, Karthik Sridharan, Ambuj Tewari
2011	J	`jnl`	Learning Kernel-Based Halfspaces with the 0-1 Loss. SIAM J. Comput. Shai Shalev-Shwartz, Ohad Shamir, Karthik Sridharan
2011	A*	`conf`	Learning Linear and Kernel Predictors with the 0-1 Loss Function. IJCAI Shai Shalev-Shwartz, Ohad Shamir, Karthik Sridharan
2011	J	`jnl`	On the Universality of Online Mirror Descent CoRR Nathan Srebro, Karthik Sridharan, Ambuj Tewari
2011	—	`conf`	On the Universality of Online Mirror Descent. NIPS Nati Srebro, Karthik Sridharan, Ambuj Tewari
2011	A*	`conf`	Online Learning: Beyond Regret. COLT Alexander Rakhlin, Karthik Sridharan, Ambuj Tewari
2011	J	`jnl`	Online Learning: Stochastic and Constrained Adversaries CoRR Alexander Rakhlin, Karthik Sridharan, Ambuj Tewari
2011	—	`conf`	Online Learning: Stochastic, Constrained, and Smoothed Adversaries. NIPS Alexander Rakhlin, Karthik Sridharan, Ambuj Tewari
2010	A*	`conf`	Convex Games in Banach Spaces. COLT Karthik Sridharan, Ambuj Tewari
2010	J	`jnl`	Learnability, Stability and Uniform Convergence. J. Mach. Learn. Res. Shai Shalev-Shwartz, Ohad Shamir, Nathan Srebro, Karthik Sridharan
2010	J	`jnl`	Learning Kernel-Based Halfspaces with the Zero-One Loss CoRR Shai Shalev-Shwartz, Ohad Shamir, Karthik Sridharan
2010	A*	`conf`	Learning Kernel-Based Halfspaces with the Zero-One Loss. COLT Shai Shalev-Shwartz, Ohad Shamir, Karthik Sridharan
2010	J	`jnl`	Online Learning: Beyond Regret CoRR Alexander Rakhlin, Karthik Sridharan, Ambuj Tewari
2010	J	`jnl`	Online Learning: Random Averages, Combinatorial Parameters, and Learnability CoRR Alexander Rakhlin, Karthik Sridharan, Ambuj Tewari
2010	—	`conf`	Online Learning: Random Averages, Combinatorial Parameters, and Learnability. NIPS Alexander Rakhlin, Karthik Sridharan, Ambuj Tewari
2010	A*	`conf`	Robust Selective Sampling from Single and Multiple Teachers. COLT Ofer Dekel, Claudio Gentile, Karthik Sridharan
2010	—	`conf`	Smoothness, Low Noise and Fast Rates. NIPS Nathan Srebro, Karthik Sridharan, Ambuj Tewari
2010	J	`jnl`	Smoothness, Low-Noise and Fast Rates CoRR Nathan Srebro, Karthik Sridharan, Ambuj Tewari
2009	A*	`conf`	Learnability and Stability in the General Learning Setting. COLT Shai Shalev-Shwartz, Ohad Shamir, Nathan Srebro, Karthik Sridharan
2009	J	`jnl`	Learning Exponential Families in High-Dimensions: Strong Convexity and Sparsity CoRR Sham M. Kakade, Ohad Shamir, Karthik Sridharan, Ambuj Tewari
2009	A*	`conf`	Multi-view clustering via canonical correlation analysis. ICML Kamalika Chaudhuri, Sham M. Kakade, Karen Livescu, Karthik Sridharan
2009	A*	`conf`	Stochastic Convex Optimization. COLT Shai Shalev-Shwartz, Ohad Shamir, Nathan Srebro, Karthik Sridharan
2009	A*	`conf`	The Complexity of Improperly Learning Large Margin Halfspaces. COLT Shai Shalev-Shwartz, Ohad Shamir, Karthik Sridharan
2008	A*	`conf`	An Information Theoretic Framework for Multi-view Learning. COLT Karthik Sridharan, Sham M. Kakade
2008	—	`conf`	Fast Rates for Regularized Objectives. NIPS Karthik Sridharan, Shai Shalev-Shwartz, Nathan Srebro
2008	—	`conf`	On the Complexity of Linear Prediction: Risk Bounds, Margin Bounds, and Regularization. NIPS Sham M. Kakade, Karthik Sridharan, Ambuj Tewari
2006	J	`jnl`	A neural network based CBIR system using STI features and relevance feedback. Intell. Data Anal. K. G. Srinivasa, Karthik Sridharan, P. Deepa Shenoy, K. R. Venugopal, Lalit M. Patnaik
2006	—	`conf`	Competitive Mixtures of Simple Neurons. ICPR (2) Karthik Sridharan, Matthew J. Beal, Venu Govindaraju
2006	—	`conf`	Identifying Handwritten Text in Mixed Documents. ICPR (2) Faisal Farooq, Karthik Sridharan, Venu Govindaraju
2005	C	`conf`	A Dynamic Migration Model for Self-adaptive Genetic Algorithms. IDEAL K. G. Srinivasa, Karthik Sridharan, P. Deepa Shenoy, K. R. Venugopal, Lalit M. Patnaik
2005	—	`conf`	A Probabilistic Approach to Semantic Face Retrieval System. AVBPA Karthik Sridharan, Sankalp Nayak, Sharat Chikkerur, Venu Govindaraju
2005	—	`conf`	A Sampling Based Approach to Facial Feature Extraction. AutoID Karthik Sridharan, Venu Govindaraju