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Sridharan, Karthik

  1. Making Gradient Descent Optimal for Strongly Convex Stochastic Optimization
    2011/09/26 by Rakhlin, Alexander, Shamir, Ohad, Sridharan, Karthik · 18 citations
    #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Optimization and Control (math.OC)
  2. Optimization, Learning, and Games with Predictable Sequences
    2013/11/08 by Alexander Rakhlin, Karthik Sridharan, Rakhlin, Alexander +1 · 21 citations
    Computer Science · Decision Sciences · #Advanced Bandit Algorithms Research #Complexity and Algorithms in Graphs #Computer Science and Game Theory (cs.GT) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Stochastic Gradient Optimization Techniques
  3. Online Learning with Predictable Sequences
    2012/08/18 by Rakhlin, Alexander, Sridharan, Karthik · 16 citations
    #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  4. Optimistic Rates for Learning with a Smooth Loss
    2010/09/20 by Nathan Srebro, Karthik Sridharan, Srebro, Nathan +3 · 10 citations
    Computer Science · Decision Sciences · Engineering · #Advanced Bandit Algorithms Research #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning and Algorithms #Sparse and Compressive Sensing Techniques
  5. Online Learning via Sequential Complexities
    2010/06/06 by Alexander Rakhlin, Karthik Sridharan, Rakhlin, Alexander +3 · 7 citations
    Computer Science · Decision Sciences · #Advanced Bandit Algorithms Research #Computability, Logic, AI Algorithms #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms
  6. Second-Order Information in Non-Convex Stochastic Optimization: Power and Limitations
    2020/06/24 by Arjevani, Yossi, Carmon, Yair, Duchi, John C. +3 · 8 citations
    #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Optimization and Control (math.OC)
  7. Adaptive Online Learning
    2015/08/21 by Dylan J. Foster, Alexander Rakhlin, Foster, Dylan J. +3 · 7 citations
    Decision Sciences · Computer Science · #Advanced Bandit Algorithms Research #Machine Learning and Algorithms #Stochastic Gradient Optimization Techniques
  8. Training Well-Generalizing Classifiers for Fairness Metrics and Other Data-Dependent Constraints
    2018/06/29 by Andrew Cotter, Cotter, Andrew, Maya R. Gupta +13 · 9 citations
    Computer Science · Social Sciences · #Explainable Artificial Intelligence (XAI) #Ethics and Social Impacts of AI #Adversarial Robustness in Machine Learning
  9. Optimization with Non-Differentiable Constraints with Applications to Fairness, Recall, Churn, and Other Goals
    2018/09/11 by Andrew Cotter, Heinrich Jiang, Cotter, Andrew +11 · 6 citations
    Computer Science · #Artificial Intelligence (cs.AI) #Computer Science and Game Theory (cs.GT) #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Optimization and Control (math.OC) #Stochastic Gradient Optimization Techniques
  10. On the Universality of Online Mirror Descent
    2011/07/20 by Nathan Srebro, Nati Srebro, Karthik Sridharan +4 · 1 voice · 5 citations
    Decision Sciences · Computer Science · #cs.LG
  11. Uniform Convergence of Gradients for Non-Convex Learning and Optimization
    2018/10/25 by Dylan J. Foster, Foster, Dylan J., Ayush Sekhari +3 · 5 citations
    Computer Science · Engineering · #Stochastic Gradient Optimization Techniques #Sparse and Compressive Sensing Techniques #Domain Adaptation and Few-Shot Learning
  12. The Complexity of Making the Gradient Small in Stochastic Convex\n Optimization
    2019/02/12 by Dylan J. Foster, Ayush Sekhari, Foster, Dylan J. +9 · 5 citations
    Computer Science · Decision Sciences · Engineering · #Advanced Bandit Algorithms Research #Complexity and Algorithms in Graphs #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Optimization and Control (math.OC) #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques
  13. Online Optimization : Competing with Dynamic Comparators
    2015/01/26 by Ali Jadbabaie, Alexander Rakhlin, Jadbabaie, Ali +5 · 4 citations
    Computer Science · Decision Sciences · #Advanced Bandit Algorithms Research #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Optimization and Control (math.OC) #Optimization and Search Problems #Reinforcement Learning in Robotics
  14. Better Mini-Batch Algorithms via Accelerated Gradient Methods
    2011/06/22 by Cotter, Andrew, Shamir, Ohad, Srebro, Nathan +1 · 3 citations
    #FOS: Computer and information sciences #Machine Learning (cs.LG)
  15. Parameter-free online learning via model selection
    2017/12/30 by Foster, Dylan J., Kale, Satyen, Mohri, Mehryar +1 · 3 citations
    #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  16. Two-Player Games for Efficient Non-Convex Constrained Optimization
    2018/04/17 by Cotter, Andrew, Jiang, Heinrich, Sridharan, Karthik · 3 citations
    #Computer Science and Game Theory (cs.GT) #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Optimization and Control (math.OC)
  17. Hypothesis Set Stability and Generalization
    2019/04/09 by Foster, Dylan J., Greenberg, Spencer, Kale, Satyen +3 · 3 citations
    #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  18. On the Complexity of Adversarial Decision Making
    2022/06/27 by Dylan J. Foster, Alexander Rakhlin, Foster, Dylan J. +5 · 4 citations
    Computer Science · Decision Sciences · #Advanced Bandit Algorithms Research #Adversarial Robustness in Machine Learning #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Optimization and Control (math.OC) #Reinforcement Learning in Robotics #Statistics Theory (math.ST)
  19. Online Nonparametric Regression with General Loss Functions
    2015/01/26 by Alexander Rakhlin, Karthik Sridharan, Rakhlin, Alexander +1 · 5 citations
    Decision Sciences · Computer Science · #Advanced Bandit Algorithms Research #Data Stream Mining Techniques #Distributed Sensor Networks and Detection Algorithms
  20. Private Causal Inference
    2015/12/17 by Matt J. Kusner, Yu Sun, Kusner, Matt J. +5 · 2 citations
    Computer Science · Mathematics · #Advanced Causal Inference Techniques #FOS: Computer and information sciences #Machine Learning (stat.ML) #Privacy-Preserving Technologies in Data #Statistical Methods and Bayesian Inference
  21. Guarantees for Epsilon-Greedy Reinforcement Learning with Function Approximation
    2022/06/19 by Christoph Dann, Dann, Christoph, Yishay Mansour +7 · 3 citations
    Computer Science · Decision Sciences · #Advanced Bandit Algorithms Research #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Reinforcement Learning in Robotics
  22. Logistic Regression: The Importance of Being Improper
    2018/03/25 by Foster, Dylan J., Kale, Satyen, Luo, Haipeng +2 · 2 citations
    #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  23. Online Learning: Sufficient Statistics and the Burkholder Method
    2018/03/20 by Dylan J. Foster, Foster, Dylan J., Alexander Rakhlin +3 · 2 citations
    Decision Sciences · Engineering · Computer Science · #Advanced Bandit Algorithms Research #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques
  24. Relax and Localize: From Value to Algorithms
    2012/04/04 by Alexander Rakhlin, Ohad Shamir, Rakhlin, Alexander +3 · 2 citations
    Decision Sciences · Computer Science · #Advanced Bandit Algorithms Research #Machine Learning and Algorithms #Reinforcement Learning in Robotics
  25. Online Learning: Stochastic and Constrained Adversaries
    2011/04/27 by Rakhlin, Alexander, Sridharan, Karthik, Tewari, Ambuj · 1 citation
    #Computer Science and Game Theory (cs.GT) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  26. On Equivalence of Martingale Tail Bounds and Deterministic Regret Inequalities
    2015/10/13 by Rakhlin, Alexander, Sridharan, Karthik · 1 citation
    #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Probability (math.PR)
  27. Learning Exponential Families in High-Dimensions: Strong Convexity and Sparsity
    2009/10/31 by Sham M. Kakade, Ohad Shamir, Kakade, Sham M. +5 · 1 citation
    Computer Science · Engineering · Mathematics · #FOS: Computer and information sciences #I.2.6 #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Sparse and Compressive Sensing Techniques #Statistical Methods and Inference
  28. SGD: The Role of Implicit Regularization, Batch-size and Multiple-epochs
    2021/07/11 by Kale, Satyen, Sekhari, Ayush, Sridharan, Karthik · 1 citation
    #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG)
  29. Online Nonparametric Regression
    2014/02/11 by Rakhlin, Alexander, Sridharan, Karthik · 1 citation
    #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Statistics Theory (math.ST)
  30. Inference in Sparse Graphs with Pairwise Measurements and Side Information
    2017/03/08 by Dylan J. Foster, Daniel Reichman, Foster, Dylan J. +3 · 1 citation
    Computer Science · Materials Science · #Topological and Geometric Data Analysis #Carbon and Quantum Dots Applications #Complexity and Algorithms in Graphs
  31. Contextual Bandits and Imitation Learning via Preference-Based Active Queries
    2023/07/24 by Ayush Sekhari, Sekhari, Ayush, Karthik Sridharan +5 · 1 citation
    Decision Sciences · Computer Science · #Advanced Bandit Algorithms Research #Machine Learning and Algorithms #Multimodal Machine Learning Applications
  32. Selective Sampling and Imitation Learning via Online Regression
    2023/07/11 by Sekhari, Ayush, Sridharan, Karthik, Sun, Wen +1 · 1 citation
    #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Statistics Theory (math.ST)
  33. Optimization, Isoperimetric Inequalities, and Sampling via Lyapunov Potentials
    2024/10/03 by Chen, August Y., Sridharan, Karthik · 1 citation
    #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Probability (math.PR) #Statistics Theory (math.ST)