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Alexey Naumov

  1. Generative Flow Networks as Entropy-Regularized RL
    2023/10/19 by Daniil Tiapkin, Tiapkin, Daniil, Н. Ф. Морозов +5 · 14 citations
    Computer Science · #Reinforcement Learning in Robotics #Explainable Artificial Intelligence (XAI)
  2. Tight High Probability Bounds for Linear Stochastic Approximation with Fixed Stepsize
    2021/06/02 by Alain Durmus, Durmus, Alain, Éric Moulines +9 · 6 citations
    Computer Science · Decision Sciences · Engineering · #Advanced Bandit Algorithms Research #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Probability (math.PR) #Sparse and Compressive Sensing Techniques #Statistics Theory (math.ST) #Stochastic Gradient Optimization Techniques
  3. Finite-time High-probability Bounds for Polyak-Ruppert Averaged Iterates of Linear Stochastic Approximation
    2022/07/10 by Alain Durmus, Éric Moulines, Durmus, Alain +5 · 6 citations
    Engineering · Mathematics · #60J20 #62L20 #Control Systems and Identification #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Markov Chains and Monte Carlo Methods #Probability (math.PR) #Statistical Methods and Inference #Statistics Theory (math.ST)
  4. Local-Global MCMC kernels: the best of both worlds
    2021/11/04 by Sergey Samsonov, Samsonov, Sergey, Evgeny Lagutin +9 · 2 citations
    Computer Science · Mathematics · #Adversarial Robustness in Machine Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Markov Chains and Monte Carlo Methods
  5. Group and Shuffle: Efficient Structured Orthogonal Parametrization
    2024/06/14 by Mikhail Gorbunov, Gorbunov, Mikhail, N. P. Yudin +9 · 5 citations
    Computer Science · #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #Computational Geometry and Mesh Generation #Computer Vision and Pattern Recognition (cs.CV) #Embedded Systems Design Techniques #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Medical Image Segmentation Techniques #Numerical Analysis (math.NA)
  6. Optimistic Posterior Sampling for Reinforcement Learning with Few Samples and Tight Guarantees
    2022/09/28 by Daniil Tiapkin, Tiapkin, Daniil, Denis Belomestny +15 · 2 citations
    Computer Science · Decision Sciences · #Advanced Bandit Algorithms Research #Age of Information Optimization #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Reinforcement Learning in Robotics
  7. Demonstration-Regularized RL
    2023/10/26 by Daniil Tiapkin, Tiapkin, Daniil, Denis Belomestny +13 · 3 citations
    Computer Science · #Adversarial Robustness in Machine Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Reinforcement Learning in Robotics
  8. SCAFFLSA: Taming Heterogeneity in Federated Linear Stochastic Approximation and TD Learning
    2024/02/06 by Paul Mangold, Sergey Samsonov, Mangold, Paul +11 · 3 citations
    Engineering · #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Optimization and Control (math.OC) #Traffic Prediction and Management Techniques
  9. Probability and moment inequalities for additive functionals of geometrically ergodic Markov chains
    2021/09/01 by Alain Durmus, Durmus, Alain, Éric Moulines +5 · 2 citations
    Mathematics · #60E15 #60J20 #65C40 #FOS: Mathematics #Geometric Analysis and Curvature Flows #Markov Chains and Monte Carlo Methods #Point processes and geometric inequalities #Probability (math.PR)
  10. Large ball probability, Gaussian comparison and anti-concentration
    2017/08/29 by Friedrich Götze, Götze, Friedrich, Alexey Naumov +5 · 2 citations
    Mathematics · Physics and Astronomy · #Advanced Statistical Methods and Models #FOS: Mathematics #Probability (math.PR) #Statistical Mechanics and Entropy #Statistical Methods and Inference
  11. From Dirichlet to Rubin: Optimistic Exploration in RL without Bonuses
    2022/05/16 by Daniil Tiapkin, Tiapkin, Daniil, Denis Belomestny +13 · 1 citation
    Computer Science · Decision Sciences · #Advanced Bandit Algorithms Research #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Reinforcement Learning in Robotics
  12. Model-free Posterior Sampling via Learning Rate Randomization
    2023/10/27 by Daniil Tiapkin, Tiapkin, Daniil, Denis Belomestny +15 · 1 citation
    Computer Science · Decision Sciences · #Advanced Bandit Algorithms Research #Bayesian Modeling and Causal Inference #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Reinforcement Learning in Robotics
  13. Rosenthal-type inequalities for linear statistics of Markov chains
    2023/03/10 by Alain Durmus, Durmus, Alain, Éric Moulines +7 · 2 citations
    Mathematics · #60E15 #60J20 #65C40 #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (stat.ML) #Markov Chains and Monte Carlo Methods #Point processes and geometric inequalities #Probability (math.PR) #Statistics Theory (math.ST) #Stochastic processes and statistical mechanics