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Rohatgi, Dhruv

  1. Self-Improvement in Language Models: The Sharpening Mechanism
    2024/12/02 by Audrey Huang, Adam Block, Huang, Audrey +13 · 2 voices · 24 citations
    Computer Science · #Natural Language Processing Techniques #Topic Modeling #cs.AI #cs.CL #cs.LG #stat.ML
  2. Near-Optimal Bounds for Online Caching with Machine Learned Advice
    2019/10/27 by Rohatgi, Dhruv · 3 citations
    #Data Structures and Algorithms (cs.DS) #FOS: Computer and information sciences
  3. Is a Good Foundation Necessary for Efficient Reinforcement Learning? The Computational Role of the Base Model in Exploration
    2025/03/10 by Dylan J. Foster, Foster, Dylan J., Zakaria Mhammedi +3 · 1 voice · 8 citations
    #cs.LG #cs.AI #cs.CL #math.ST
  4. Computational-Statistical Tradeoffs at the Next-Token Prediction Barrier: Autoregressive and Imitation Learning under Misspecification
    2025/02/18 by Dhruv Rohatgi, Rohatgi, Dhruv, Adam Block +7 · 1 voice · 7 citations
    Computer Science · #Natural Language Processing Techniques
  5. Provably Auditing Ordinary Least Squares in Low Dimensions
    2022/05/28 by Ankur Moitra, Moitra, Ankur, Dhruv Rohatgi +1 · 3 citations
    Mathematics · #Advanced Statistical Methods and Models #Data Structures and Algorithms (cs.DS) #Econometrics (econ.EM) #FOS: Computer and information sciences #FOS: Economics and business #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Statistical Methods and Inference #Statistical and numerical algorithms
  6. Provable benefits of score matching
    2023/06/03 by Chirag Pabbaraju, Pabbaraju, Chirag, Dhruv Rohatgi +9 · 3 citations
    Computer Science · Engineering · Mathematics · #Data Structures and Algorithms (cs.DS) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Sparse and Compressive Sensing Techniques #Statistical Methods and Inference #Stochastic Gradient Optimization Techniques
  7. Lasso with Latents: Efficient Estimation, Covariate Rescaling, and Computational-Statistical Gaps
    2024/02/23 by Kelner, Jonathan, Koehler, Frederic, Meka, Raghu +1 · 3 citations
    #Computational Complexity (cs.CC) #Data Structures and Algorithms (cs.DS) #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Statistics Theory (math.ST)
  8. Off-diagonal ordered Ramsey numbers of matchings
    2018/08/13 by Rohatgi, Dhruv · 1 citation
    #Combinatorics (math.CO) #FOS: Mathematics
  9. Learning in Observable POMDPs, without Computationally Intractable Oracles
    2022/06/07 by Noah Golowich, Ankur Moitra, Golowich, Noah +3 · 2 citations
    Computer Science · #Artificial Intelligence (cs.AI) #Bayesian Modeling and Causal Inference #Data Structures and Algorithms (cs.DS) #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Optimization and Control (math.OC) #Reinforcement Learning in Robotics
  10. Truncated Linear Regression in High Dimensions
    2020/07/29 by Daskalakis, Constantinos, Rohatgi, Dhruv, Zampetakis, Manolis · 1 citation
    #Data Structures and Algorithms (cs.DS) #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Statistics Theory (math.ST)
  11. On the Power of Preconditioning in Sparse Linear Regression
    2021/06/17 by Jonathan A. Kelner, Frederic Koehler, Kelner, Jonathan +5 · 1 citation
    Engineering · Mathematics · Computer Science · #Sparse and Compressive Sensing Techniques #Statistical Methods and Inference #Stochastic Gradient Optimization Techniques
  12. Planning in Observable POMDPs in Quasipolynomial Time
    2022/01/12 by Noah Golowich, Ankur Moitra, Golowich, Noah +3 · 1 citation
    Computer Science · #Reinforcement Learning in Robotics
  13. Feature Adaptation for Sparse Linear Regression
    2023/05/26 by Kelner, Jonathan, Koehler, Frederic, Meka, Raghu +1 · 1 citation
    #Data Structures and Algorithms (cs.DS) #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Statistics Theory (math.ST)
  14. Exploration is Harder than Prediction: Cryptographically Separating Reinforcement Learning from Supervised Learning
    2024/04/04 by Noah Golowich, Ankur Moitra, Golowich, Noah +3 · 1 citation
    Computer Science · #Adversarial Robustness in Machine Learning #Blockchain Technology Applications and Security #Computability, Logic, AI Algorithms #Computational Complexity (cs.CC) #Cryptography and Security (cs.CR) #Data Structures and Algorithms (cs.DS) #FOS: Computer and information sciences #Machine Learning (cs.LG)
  15. Necessary and Sufficient Oracles: Toward a Computational Taxonomy For Reinforcement Learning
    2025/02/12 by Dhruv Rohatgi, Rohatgi, Dhruv, Dylan J. Foster +1 · 1 voice · 1 citation
    Computer Science · #Computability, Logic, AI Algorithms #Evolutionary Algorithms and Applications #cs.CC #cs.LG