Karthik Sridharan

Affiliations:
  • University at Buffalo, USA


According to our database1, Karthik Sridharan authored at least 81 papers between 2005 and 2023.

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Bibliography

2023
Contextual Bandits and Imitation Learning via Preference-Based Active Queries.
CoRR, 2023

Selective Sampling and Imitation Learning via Online Regression.
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.
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.
Math. Oper. Res., 2022

From Gradient Flow on Population Loss to Learning with Stochastic Gradient Descent.
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.
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.
Proceedings of the International Conference on Machine Learning, 2022

2021
SGD: The Role of Implicit Regularization, Batch-size and Multiple-epochs.
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.
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.
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.
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.
Proceedings of the Conference on Learning Theory, 2020

2019
Optimization with Non-Differentiable Constraints with Applications to Fairness, Recall, Churn, and Other Goals.
J. Mach. Learn. Res., 2019

Hypothesis Set Stability and Generalization.
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.
Proceedings of the 36th International Conference on Machine Learning, 2019

Distributed Learning with Sublinear Communication.
Proceedings of the 36th International Conference on Machine Learning, 2019

The Complexity of Making the Gradient Small in Stochastic Convex Optimization.
Proceedings of the Conference on Learning Theory, 2019

Two-Player Games for Efficient Non-Convex Constrained Optimization.
Proceedings of the Algorithmic Learning Theory, 2019

2018
Uniform Convergence of Gradients for Non-Convex Learning and Optimization.
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.
Proceedings of the Conference On Learning Theory, 2018

Logistic Regression: The Importance of Being Improper.
Proceedings of the Conference On Learning Theory, 2018

Inference in Sparse Graphs with Pairwise Measurements and Side Information.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017
Parameter-Free Online Learning via Model Selection.
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.
Proceedings of the 30th Conference on Learning Theory, 2017

ZigZag: A New Approach to Adaptive Online Learning.
Proceedings of the 30th Conference on Learning Theory, 2017

Efficient Online Multiclass Prediction on Graphs via Surrogate Losses.
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.
CoRR, 2016

Fast Convergence of Common Learning Algorithms in Games.
CoRR, 2016

Exploiting the Structure: Stochastic Gradient Methods Using Raw Clusters.
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.
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.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Private Causal Inference.
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

2015
Online learning via sequential complexities.
J. Mach. Learn. Res., 2015

Online Nonparametric Regression with General Loss Functions.
CoRR, 2015

Sequential Probability Assignment with Binary Alphabets and Large Classes of Experts.
CoRR, 2015

Adaptive Online Learning.
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.
Proceedings of The 28th Conference on Learning Theory, 2015

Learning with Square Loss: Localization through Offset Rademacher Complexity.
Proceedings of The 28th Conference on Learning Theory, 2015

Online Optimization : Competing with Dynamic Comparators.
Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

2014
Online Nonparametric Regression.
CoRR, 2014

Online Non-Parametric Regression.
Proceedings of The 27th Conference on Learning Theory, 2014

2013
Empirical Entropy, Minimax Regret and Minimax Risk.
CoRR, 2013

Optimization, Learning, and Games with Predictable Sequences.
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.
Proceedings of the 2013 IEEE Information Theory Workshop, 2013

Online Learning with Predictable Sequences.
Proceedings of the COLT 2013, 2013

Competing With Strategies.
Proceedings of the COLT 2013, 2013

Localization and Adaptation in Online Learning.
Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, 2013

2012
Selective sampling and active learning from single and multiple teachers.
J. Mach. Learn. Res., 2012

Learning From An Optimization Viewpoint
CoRR, 2012

Relax and Localize: From Value to Algorithms
CoRR, 2012

Relax and Randomize : From Value to Algorithms.
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.
Proceedings of the 29th International Conference on Machine Learning, 2012

Minimizing The Misclassification Error Rate Using a Surrogate Convex Loss.
Proceedings of the 29th International Conference on Machine Learning, 2012

2011
Learning Kernel-Based Halfspaces with the 0-1 Loss.
SIAM J. Comput., 2011

Online Learning: Beyond Regret.
Proceedings of the COLT 2011, 2011

Complexity-Based Approach to Calibration with Checking Rules.
Proceedings of the COLT 2011, 2011

Online Learning: Stochastic and Constrained Adversaries
CoRR, 2011

On the Universality of Online Mirror Descent.
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.
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.
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.
Proceedings of the IJCAI 2011, 2011

2010
Learnability, Stability and Uniform Convergence.
J. Mach. Learn. Res., 2010

Smoothness, Low Noise and Fast Rates.
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.
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.
Proceedings of the COLT 2010, 2010

Learning Kernel-Based Halfspaces with the Zero-One Loss.
Proceedings of the COLT 2010, 2010

Robust Selective Sampling from Single and Multiple Teachers.
Proceedings of the COLT 2010, 2010

2009
Learning Exponential Families in High-Dimensions: Strong Convexity and Sparsity
CoRR, 2009

Multi-view clustering via canonical correlation analysis.
Proceedings of the 26th Annual International Conference on Machine Learning, 2009

Learnability and Stability in the General Learning Setting.
Proceedings of the COLT 2009, 2009

Stochastic Convex Optimization.
Proceedings of the COLT 2009, 2009

The Complexity of Improperly Learning Large Margin Halfspaces.
Proceedings of the COLT 2009, 2009

2008
Fast Rates for Regularized Objectives.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

On the Complexity of Linear Prediction: Risk Bounds, Margin Bounds, and Regularization.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

An Information Theoretic Framework for Multi-view Learning.
Proceedings of the 21st Annual Conference on Learning Theory, 2008

2006
A neural network based CBIR system using STI features and relevance feedback.
Intell. Data Anal., 2006

Competitive Mixtures of Simple Neurons.
Proceedings of the 18th International Conference on Pattern Recognition (ICPR 2006), 2006

Identifying Handwritten Text in Mixed Documents.
Proceedings of the 18th International Conference on Pattern Recognition (ICPR 2006), 2006

2005
A Dynamic Migration Model for Self-adaptive Genetic Algorithms.
Proceedings of the Intelligent Data Engineering and Automated Learning, 2005

A Probabilistic Approach to Semantic Face Retrieval System.
Proceedings of the Audio- and Video-Based Biometric Person Authentication, 2005

A Sampling Based Approach to Facial Feature Extraction.
Proceedings of the Fourth IEEE Workshop on Automatic Identification Advanced Technologies (AutoID 2005), 2005


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