Karthik Sridharan

According to our database, Karthik Sridharan authored at least 84 papers between 2005 and 2024.

Collaborative distances:

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

2024

From Optimization to Sampling via Lyapunov Potentials.

August Y. Chen, Karthik Sridharan

CoRR, 2024

Langevin Dynamics: A Unified Perspective on Optimization via Lyapunov Potentials.

August Y. Chen, Ayush Sekhari, Karthik Sridharan

CoRR, 2024

Online Learning with Unknown Constraints.

Karthik Sridharan, Seung Won Wilson Yoo

CoRR, 2024

2023

Contextual Bandits and Imitation Learning via Preference-Based Active Queries.

Ayush Sekhari, Karthik Sridharan, Wen Sun, Runzhe Wu

CoRR, 2023

Selective Sampling and Imitation Learning via Online Regression.

Ayush Sekhari, Karthik Sridharan, Wen Sun, Runzhe Wu

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

Contextual Bandits and Imitation Learning with Preference-Based Active Queries.

Ayush Sekhari, Karthik Sridharan, Wen Sun, Runzhe Wu

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

2022

Small-Loss Bounds for Online Learning with Partial Information.

Thodoris Lykouris, Karthik Sridharan, Éva Tardos

Math. Oper. Res., 2022

From Gradient Flow on Population Loss to Learning with Stochastic Gradient Descent.

Christopher De Sa, Satyen Kale, Jason D. Lee, Ayush Sekhari, Karthik Sridharan

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

On the Complexity of Adversarial Decision Making.

Dylan J. Foster, Alexander Rakhlin, Ayush Sekhari, Karthik Sridharan

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

Guarantees for Epsilon-Greedy Reinforcement Learning with Function Approximation.

Christoph Dann, Yishay Mansour, Mehryar Mohri, Ayush Sekhari, Karthik Sridharan

Proceedings of the International Conference on Machine Learning, 2022

2021

SGD: The Role of Implicit Regularization, Batch-size and Multiple-epochs.

Ayush Sekhari, Karthik Sridharan, Satyen Kale

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Agnostic Reinforcement Learning with Low-Rank MDPs and Rich Observations.

Ayush Sekhari, Christoph Dann, Mehryar Mohri, Yishay Mansour, Karthik Sridharan

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

Reinforcement Learning with Feedback Graphs.

Christoph Dann, Yishay Mansour, Mehryar Mohri, Ayush Sekhari, Karthik Sridharan

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Online learning with dynamics: A minimax perspective.

Kush Bhatia, Karthik Sridharan

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 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

Proceedings of the Conference on Learning Theory, 2020

2019

Optimization with Non-Differentiable Constraints with Applications to Fairness, Recall, Churn, and Other Goals.

Andrew Cotter, Heinrich Jiang, Maya R. Gupta, Serena Lutong Wang, Taman Narayan, Seungil You, Karthik Sridharan

J. Mach. Learn. Res., 2019

Hypothesis Set Stability and Generalization.

Dylan J. Foster, Spencer Greenberg, Satyen Kale, Haipeng Luo, Mehryar Mohri, Karthik Sridharan

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

Training Well-Generalizing Classifiers for Fairness Metrics and Other Data-Dependent Constraints.

Andrew Cotter, Maya R. Gupta, Heinrich Jiang, Nathan Srebro, Karthik Sridharan, Serena Lutong Wang, Blake E. Woodworth, Seungil You

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

Distributed Learning with Sublinear Communication.

Jayadev Acharya, Chris De Sa, Dylan J. Foster, Karthik Sridharan

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

The Complexity of Making the Gradient Small in Stochastic Convex Optimization.

Dylan J. Foster, Ayush Sekhari, Ohad Shamir, Nathan Srebro, Karthik Sridharan, Blake E. Woodworth

Proceedings of the Conference on Learning Theory, 2019

Two-Player Games for Efficient Non-Convex Constrained Optimization.

Andrew Cotter, Heinrich Jiang, Karthik Sridharan

Proceedings of the Algorithmic Learning Theory, 2019

2018

Uniform Convergence of Gradients for Non-Convex Learning and Optimization.

Dylan J. Foster, Ayush Sekhari, Karthik Sridharan

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Online Learning: Sufficient Statistics and the Burkholder Method.

Dylan J. Foster, Alexander Rakhlin, Karthik Sridharan

Proceedings of the Conference On Learning Theory, 2018

Logistic Regression: The Importance of Being Improper.

Dylan J. Foster, Satyen Kale, Haipeng Luo, Mehryar Mohri, Karthik Sridharan

Proceedings of the Conference On Learning Theory, 2018

Inference in Sparse Graphs with Pairwise Measurements and Side Information.

Dylan J. Foster, Karthik Sridharan, Daniel Reichman

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017

Parameter-Free Online Learning via Model Selection.

Dylan J. Foster, Satyen Kale, Mehryar Mohri, Karthik Sridharan

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

On Equivalence of Martingale Tail Bounds and Deterministic Regret Inequalities.

Alexander Rakhlin, Karthik Sridharan

Proceedings of the 30th Conference on Learning Theory, 2017

ZigZag: A New Approach to Adaptive Online Learning.

Dylan J. Foster, Alexander Rakhlin, Karthik Sridharan

Proceedings of the 30th Conference on Learning Theory, 2017

Efficient Online Multiclass Prediction on Graphs via Surrogate Losses.

Alexander Rakhlin, Karthik Sridharan

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

2016

A Tutorial on Online Supervised Learning with Applications to Node Classification in Social Networks.

Alexander Rakhlin, Karthik Sridharan

CoRR, 2016

Fast Convergence of Common Learning Algorithms in Games.

Dylan J. Foster, Zhiyuan Li, Thodoris Lykouris, Karthik Sridharan, Éva Tardos

CoRR, 2016

Exploiting the Structure: Stochastic Gradient Methods Using Raw Clusters.

Zeyuan Allen Zhu, Yang Yuan, Karthik Sridharan

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Learning in Games: Robustness of Fast Convergence.

Dylan J. Foster, Zhiyuan Li, Thodoris Lykouris, Karthik Sridharan, Éva Tardos

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

BISTRO: An Efficient Relaxation-Based Method for Contextual Bandits.

Alexander Rakhlin, Karthik Sridharan

Proceedings of the 33nd International Conference on Machine Learning, 2016

Private Causal Inference.

Matt J. Kusner, Yu Sun, Karthik Sridharan, Kilian Q. Weinberger

Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

2015

Online learning via sequential complexities.

Alexander Rakhlin, Karthik Sridharan, Ambuj Tewari

J. Mach. Learn. Res., 2015

Online Nonparametric Regression with General Loss Functions.

Alexander Rakhlin, Karthik Sridharan

CoRR, 2015

Sequential Probability Assignment with Binary Alphabets and Large Classes of Experts.

Alexander Rakhlin, Karthik Sridharan

CoRR, 2015

Adaptive Online Learning.

Dylan J. Foster, Alexander Rakhlin, Karthik Sridharan

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Hierarchies of Relaxations for Online Prediction Problems with Evolving Constraints.

Alexander Rakhlin, Karthik Sridharan

Proceedings of The 28th Conference on Learning Theory, 2015

Learning with Square Loss: Localization through Offset Rademacher Complexity.

Tengyuan Liang, Alexander Rakhlin, Karthik Sridharan

Proceedings of The 28th Conference on Learning Theory, 2015

Online Optimization : Competing with Dynamic Comparators.

Ali Jadbabaie, Alexander Rakhlin, Shahin Shahrampour, Karthik Sridharan

Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

2014

Online Nonparametric Regression.

Alexander Rakhlin, Karthik Sridharan

CoRR, 2014

Online Non-Parametric Regression.

Alexander Rakhlin, Karthik Sridharan

Proceedings of The 27th Conference on Learning Theory, 2014

2013

Empirical Entropy, Minimax Regret and Minimax Risk.

Alexander Rakhlin, Karthik Sridharan, Alexandre B. Tsybakov

CoRR, 2013

Optimization, Learning, and Games with Predictable Sequences.

Alexander Rakhlin, Karthik Sridharan

Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

On Semi-Probabilistic universal prediction.

Alexander Rakhlin, Karthik Sridharan

Proceedings of the 2013 IEEE Information Theory Workshop, 2013

Online Learning with Predictable Sequences.

Alexander Rakhlin, Karthik Sridharan

Proceedings of the COLT 2013, 2013

Competing With Strategies.

Wei Han, Alexander Rakhlin, Karthik Sridharan

Proceedings of the COLT 2013, 2013

Localization and Adaptation in Online Learning.

Alexander Rakhlin, Ohad Shamir, Karthik Sridharan

Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, 2013

2012

Selective sampling and active learning from single and multiple teachers.

Ofer Dekel, Claudio Gentile, Karthik Sridharan

J. Mach. Learn. Res., 2012

Learning From An Optimization Viewpoint

Karthik Sridharan

CoRR, 2012

Relax and Localize: From Value to Algorithms

Alexander Rakhlin, Ohad Shamir, Karthik Sridharan

CoRR, 2012

Relax and Randomize : From Value to Algorithms.

Alexander Rakhlin, Ohad Shamir, Karthik Sridharan

Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Making Gradient Descent Optimal for Strongly Convex Stochastic Optimization.

Alexander Rakhlin, Ohad Shamir, Karthik Sridharan

Proceedings of the 29th International Conference on Machine Learning, 2012

Minimizing The Misclassification Error Rate Using a Surrogate Convex Loss.

Shai Ben-David, David Loker, Nathan Srebro, Karthik Sridharan

Proceedings of the 29th International Conference on Machine Learning, 2012

2011

Learning Kernel-Based Halfspaces with the 0-1 Loss.

Shai Shalev-Shwartz, Ohad Shamir, Karthik Sridharan

SIAM J. Comput., 2011

Online Learning: Beyond Regret.

Alexander Rakhlin, Karthik Sridharan, Ambuj Tewari

Proceedings of the COLT 2011, 2011

Complexity-Based Approach to Calibration with Checking Rules.

Dean P. Foster, Alexander Rakhlin, Karthik Sridharan, Ambuj Tewari

Proceedings of the COLT 2011, 2011

Online Learning: Stochastic and Constrained Adversaries

Alexander Rakhlin, Karthik Sridharan, Ambuj Tewari

CoRR, 2011

On the Universality of Online Mirror Descent.

Nati Srebro, Karthik Sridharan, Ambuj Tewari

Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Online Learning: Stochastic, Constrained, and Smoothed Adversaries.

Alexander Rakhlin, Karthik Sridharan, Ambuj Tewari

Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Better Mini-Batch Algorithms via Accelerated Gradient Methods.

Andrew Cotter, Ohad Shamir, Nati Srebro, Karthik Sridharan

Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Learning Linear and Kernel Predictors with the 0-1 Loss Function.

Shai Shalev-Shwartz, Ohad Shamir, Karthik Sridharan

Proceedings of the IJCAI 2011, 2011

2010

Learnability, Stability and Uniform Convergence.

Shai Shalev-Shwartz, Ohad Shamir, Nathan Srebro, Karthik Sridharan

J. Mach. Learn. Res., 2010

Smoothness, Low Noise and Fast Rates.

Nathan Srebro, Karthik Sridharan, Ambuj Tewari

Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Online Learning: Random Averages, Combinatorial Parameters, and Learnability.

Alexander Rakhlin, Karthik Sridharan, Ambuj Tewari

Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Convex Games in Banach Spaces.

Karthik Sridharan, Ambuj Tewari

Proceedings of the COLT 2010, 2010

Learning Kernel-Based Halfspaces with the Zero-One Loss.

Shai Shalev-Shwartz, Ohad Shamir, Karthik Sridharan

Proceedings of the COLT 2010, 2010

Robust Selective Sampling from Single and Multiple Teachers.

Ofer Dekel, Claudio Gentile, Karthik Sridharan

Proceedings of the COLT 2010, 2010

2009

Learning Exponential Families in High-Dimensions: Strong Convexity and Sparsity

Sham M. Kakade, Ohad Shamir, Karthik Sridharan, Ambuj Tewari

CoRR, 2009

Multi-view clustering via canonical correlation analysis.

Kamalika Chaudhuri, Sham M. Kakade, Karen Livescu, Karthik Sridharan

Proceedings of the 26th Annual International Conference on Machine Learning, 2009

Learnability and Stability in the General Learning Setting.

Shai Shalev-Shwartz, Ohad Shamir, Nathan Srebro, Karthik Sridharan

Proceedings of the COLT 2009, 2009

Stochastic Convex Optimization.

Shai Shalev-Shwartz, Ohad Shamir, Nathan Srebro, Karthik Sridharan

Proceedings of the COLT 2009, 2009

The Complexity of Improperly Learning Large Margin Halfspaces.

Shai Shalev-Shwartz, Ohad Shamir, Karthik Sridharan

Proceedings of the COLT 2009, 2009

2008

Fast Rates for Regularized Objectives.

Karthik Sridharan, Shai Shalev-Shwartz, Nathan Srebro

Proceedings of the Advances in Neural Information Processing Systems 21, 2008

On the Complexity of Linear Prediction: Risk Bounds, Margin Bounds, and Regularization.

Sham M. Kakade, Karthik Sridharan, Ambuj Tewari

Proceedings of the Advances in Neural Information Processing Systems 21, 2008

An Information Theoretic Framework for Multi-view Learning.

Karthik Sridharan, Sham M. Kakade

Proceedings of the 21st Annual Conference on Learning Theory, 2008

2006

A neural network based CBIR system using STI features and relevance feedback.

K. G. Srinivasa, Karthik Sridharan, P. Deepa Shenoy, K. R. Venugopal, Lalit M. Patnaik

Intell. Data Anal., 2006

Competitive Mixtures of Simple Neurons.

Karthik Sridharan, Matthew J. Beal, Venu Govindaraju

Proceedings of the 18th International Conference on Pattern Recognition (ICPR 2006), 2006

Identifying Handwritten Text in Mixed Documents.

Faisal Farooq, Karthik Sridharan, Venu Govindaraju

Proceedings of the 18th International Conference on Pattern Recognition (ICPR 2006), 2006

2005

A Dynamic Migration Model for Self-adaptive Genetic Algorithms.

K. G. Srinivasa, Karthik Sridharan, P. Deepa Shenoy, K. R. Venugopal, Lalit M. Patnaik

Proceedings of the Intelligent Data Engineering and Automated Learning, 2005

A Probabilistic Approach to Semantic Face Retrieval System.

Karthik Sridharan, Sankalp Nayak, Sharat Chikkerur, Venu Govindaraju

Proceedings of the Audio- and Video-Based Biometric Person Authentication, 2005

A Sampling Based Approach to Facial Feature Extraction.

Karthik Sridharan, Venu Govindaraju

Proceedings of the Fourth IEEE Workshop on Automatic Identification Advanced Technologies (AutoID 2005), 2005