Sergey Samsonov

1. 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)
2. Tight High Probability Bounds for Linear Stochastic Approximation with Fixed Stepsize
   2021/06/02 by Alain Durmus, Durmus, Alain, Éric Moulines +9 · 5 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. 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
4. 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)
5. From Dirichlet to Rubin: Optimistic Exploration in RL without Bonuses
   2022/05/16 by Daniil Tiapkin, Denis Belomestny, Tiapkin, Daniil +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
6. Improving GFlowNets with Monte Carlo Tree Search
   2024/06/19 by Н. Ф. Морозов, Morozov, Nikita, Daniil Tiapkin +7 · 2 citations
   Computer Science · #Artificial Intelligence (cs.AI) #Data Stream Mining Techniques #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Neural Networks and Applications
7. Statistical inference for Linear Stochastic Approximation with Markovian Noise
   2025/05/25 by Sergey Samsonov, Marina Sheshukova, Samsonov, Sergey +5 · 4 citations
   Decision Sciences · #60F05 #62E20 #62L20 #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Optimization and Control (math.OC) #Probabilistic and Robust Engineering Design #Statistics Theory (math.ST)
8. Rosenthal-type inequalities for linear statistics of Markov chains
   2023/03/10 by Alain Durmus, Éric Moulines, Durmus, Alain +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