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Alexander Rakhlin

Identifiers

  • name variant Alexander Rakhlin 0.60 · backfill

Papers (104)

  1. Learning with Simulators: No Regret in a Computationally Bounded World cs.LG · 2026 · author #4
  2. The Sample Complexity of Multiclass and Sparse Contextual Bandits cs.LG · 2026 · author #7
  3. Self-Normalized Martingales and Uniform Regret Bounds for Linear Regression stat.ML · 2026 · author #3
  4. End-to-End Efficient RL for Linear Bellman Complete MDPs with Deterministic Transitions cs.LG · 2026 · author #2
  5. Demonstration Experiments math.ST · 2026 · author #3
  6. High-accuracy log-concave sampling with stochastic queries math.ST · 2026 · author #4
  7. High-accuracy sampling for diffusion models and log-concave distributions cs.LG · 2026 · author #4
  8. Outcome-Based Online Reinforcement Learning: Algorithms and Fundamental Limits cs.LG · 2025 · author #3
  9. On the Minimax Regret of Sequential Probability Assignment via Square-Root Entropy cs.LG · 2025 · author #3
  10. Do We Need to Verify Step by Step? Rethinking Process Supervision from a Theoretical Perspective cs.LG · 2025 · author #2
  11. Decision Making in Changing Environments: Robustness, Query-Based Learning, and Differential Privacy cs.LG · 2025 · author #2
  12. GaussMark: A Practical Approach for Structural Watermarking of Language Models cs.CR · 2025 · author #3
  13. Refined Risk Bounds for Unbounded Losses via Transductive Priors stat.ML · 2024 · author #2
  14. How Does Variance Shape the Regret in Contextual Bandits? cs.LG · 2024 · author #3
  15. Assouad, Fano, and Le Cam with Interaction: A Unifying Lower Bound Framework and Characterization for Bandit Learnability cs.LG · 2024 · author #5
  16. Random Latent Exploration for Deep Reinforcement Learning cs.LG · 2024 · author #4
  17. Near-Optimal Learning and Planning in Separated Latent MDPs cs.LG · 2024 · author #4
  18. Exploratory Preference Optimization: Harnessing Implicit Q*-Approximation for Sample-Efficient RLHF cs.LG · 2024 · author #6
  19. The Power of Resets in Online Reinforcement Learning cs.LG · 2024 · author #3
  20. Online Estimation via Offline Estimation: An Information-Theoretic Framework stat.ML · 2024 · author #4
  21. Offline Reinforcement Learning: Role of State Aggregation and Trajectory Data cs.LG · 2024 · author #2
  22. On the Performance of Empirical Risk Minimization with Smoothed Data stat.ML · 2024 · author #2
  23. Foundations of Reinforcement Learning and Interactive Decision Making cs.LG · 2023 · author #2
  24. When is Agnostic Reinforcement Learning Statistically Tractable? cs.LG · 2023 · author #3
  25. Efficient Model-Free Exploration in Low-Rank MDPs cs.LG · 2023 · author #4
  26. Convex and Non-convex Optimization Under Generalized Smoothness math.OC · 2023 · author #4
  27. On the Complexity of Multi-Agent Decision Making: From Learning in Games to Partial Monitoring cs.LG · 2023 · author #4
  28. Convergence of Adam Under Relaxed Assumptions math.OC · 2023 · author #2
  29. Representation Learning with Multi-Step Inverse Kinematics: An Efficient and Optimal Approach to Rich-Observation RL cs.LG · 2023 · author #3
  30. Tight Bounds for $\gamma$-Regret via the Decision-Estimation Coefficient cs.LG · 2023 · author #2
  31. Oracle-Efficient Smoothed Online Learning for Piecewise Continuous Decision Making stat.ML · 2023 · author #2
  32. Model-Free Reinforcement Learning with the Decision-Estimation Coefficient cs.LG · 2022 · author #4
  33. On the Complexity of Adversarial Decision Making cs.LG · 2022 · author #2
  34. Rate of convergence of the smoothed empirical Wasserstein distance math.PR · 2022 · author #4
  35. Damped Online Newton Step for Portfolio Selection cs.LG · 2022 · author #2
  36. Smoothed Online Learning is as Easy as Statistical Learning stat.ML · 2022 · author #4
  37. The Statistical Complexity of Interactive Decision Making cs.LG · 2021 · author #4
  38. On Submodular Contextual Bandits cs.LG · 2021 · author #2
  39. Intrinsic Dimension Estimation Using Wasserstein Distances stat.ML · 2021 · author #4
  40. Deep learning: a statistical viewpoint math.ST · 2021 · author #3
  41. On the Minimal Error of Empirical Risk Minimization math.ST · 2021 · author #2
  42. Top-$k$ eXtreme Contextual Bandits with Arm Hierarchy stat.ML · 2021 · author #2
  43. Learning the Linear Quadratic Regulator from Nonlinear Observations cs.LG · 2020 · author #7
  44. Instance-Dependent Complexity of Contextual Bandits and Reinforcement Learning: A Disagreement-Based Perspective cs.LG · 2020 · author #2
  45. Fast Mixing of Multi-Scale Langevin Dynamics under the Manifold Hypothesis stat.ML · 2020 · author #3
  46. On Suboptimality of Least Squares with Application to Estimation of Convex Bodies math.ST · 2020 · author #2
  47. Learning nonlinear dynamical systems from a single trajectory cs.LG · 2020 · author #2
  48. Beyond UCB: Optimal and Efficient Contextual Bandits with Regression Oracles cs.LG · 2020 · author #2
  49. Generative Modeling with Denoising Auto-Encoders and Langevin Sampling stat.ML · 2020 · author #3
  50. $\ell_{\infty}$ Vector Contraction for Rademacher Complexity cs.LG · 2019 · author #2
  51. Data Driven Estimation of Stochastic Switched Linear Systems of Unknown Order eess.SY · 2019 · author #2
  52. On the Multiple Descent of Minimum-Norm Interpolants and Restricted Lower Isometry of Kernels math.ST · 2019 · author #2
  53. Breast Tumor Cellularity Assessment using Deep Neural Networks eess.IV · 2019 · author #1
  54. Optimality of Maximum Likelihood for Log-Concave Density Estimation and Bounded Convex Regression math.ST · 2019 · author #3
  55. Nonparametric Finite Time LTI System Identification eess.SY · 2019 · author #2
  56. Consistency of Interpolation with Laplace Kernels is a High-Dimensional Phenomenon stat.ML · 2018 · author #1
  57. Near optimal finite time identification of arbitrary linear dynamical systems cs.SY · 2018 · author #2
  58. Just Interpolate: Kernel "Ridgeless" Regression Can Generalize math.ST · 2018 · author #2
  59. Does data interpolation contradict statistical optimality? stat.ML · 2018 · author #2
  60. Angiodysplasia Detection and Localization Using Deep Convolutional Neural Networks cs.CV · 2018 · author #3
  61. Online Learning: Sufficient Statistics and the Burkholder Method cs.LG · 2018 · author #2
  62. Automatic Instrument Segmentation in Robot-Assisted Surgery Using Deep Learning cs.CV · 2018 · author #2
  63. Deep Convolutional Neural Networks for Breast Cancer Histology Image Analysis cs.CV · 2018 · author #1
  64. Theory of Deep Learning IIb: Optimization Properties of SGD cs.LG · 2018 · author #3
  65. Size-Independent Sample Complexity of Neural Networks cs.LG · 2017 · author #2
  66. Pediatric Bone Age Assessment Using Deep Convolutional Neural Networks cs.CV · 2017 · author #2
  67. Fisher-Rao Metric, Geometry, and Complexity of Neural Networks cs.LG · 2017 · author #3
  68. Weighted Message Passing and Minimum Energy Flow for Heterogeneous Stochastic Block Models with Side Information math.ST · 2017 · author #3
  69. ZigZag: A new approach to adaptive online learning cs.LG · 2017 · author #2
  70. Non-convex learning via Stochastic Gradient Langevin Dynamics: a nonasymptotic analysis cs.LG · 2017 · author #2
  71. A Tutorial on Online Supervised Learning with Applications to Node Classification in Social Networks cs.LG · 2016 · author #1
  72. On Detection and Structural Reconstruction of Small-World Random Networks math.ST · 2016 · author #3
  73. Inference via Message Passing on Partially Labeled Stochastic Block Models math.ST · 2016 · author #3
  74. Distributed Estimation of Dynamic Parameters : Regret Analysis math.OC · 2016 · author #2
  75. BISTRO: An Efficient Relaxation-Based Method for Contextual Bandits cs.LG · 2016 · author #1
  76. Finite-time Analysis of the Distributed Detection Problem cs.SY · 2015 · author #2
  77. On Equivalence of Martingale Tail Bounds and Deterministic Regret Inequalities math.PR · 2015 · author #1
  78. Adaptive Online Learning cs.LG · 2015 · author #2
  79. Hierarchies of Relaxations for Online Prediction Problems with Evolving Constraints cs.LG · 2015 · author #1
  80. Learning with Square Loss: Localization through Offset Rademacher Complexity stat.ML · 2015 · author #2
  81. Computational and Statistical Boundaries for Submatrix Localization in a Large Noisy Matrix math.ST · 2015 · author #3
  82. Sequential Probability Assignment with Binary Alphabets and Large Classes of Experts cs.IT · 2015 · author #1
  83. Escaping the Local Minima via Simulated Annealing: Optimization of Approximately Convex Functions math.NA · 2015 · author #4
  84. Online Nonparametric Regression with General Loss Functions stat.ML · 2015 · author #1
  85. Online Optimization : Competing with Dynamic Comparators cs.LG · 2015 · author #2
  86. Distributed Detection : Finite-time Analysis and Impact of Network Topology math.OC · 2014 · author #2
  87. Geometric Inference for General High-Dimensional Linear Inverse Problems math.ST · 2014 · author #3
  88. On Zeroth-Order Stochastic Convex Optimization via Random Walks cs.LG · 2014 · author #3
  89. Online Nonparametric Regression stat.ML · 2014 · author #1
  90. Optimization, Learning, and Games with Predictable Sequences cs.LG · 2013 · author #1
  91. Online Learning of Dynamic Parameters in Social Networks math.OC · 2013 · author #2
  92. Efficient Sampling from Time-Varying Log-Concave Distributions stat.ML · 2013 · author #2
  93. Empirical entropy, minimax regret and minimax risk math.ST · 2013 · author #1
  94. Competing With Strategies stat.ML · 2013 · author #2
  95. Online Learning with Predictable Sequences stat.ML · 2012 · author #1
  96. Relax and Localize: From Value to Algorithms cs.LG · 2012 · author #1
  97. Making Gradient Descent Optimal for Strongly Convex Stochastic Optimization cs.LG · 2011 · author #1
  98. No Internal Regret via Neighborhood Watch cs.LG · 2011 · author #2
  99. Stochastic convex optimization with bandit feedback math.OC · 2011 · author #5
  100. Online Learning: Stochastic and Constrained Adversaries stat.ML · 2011 · author #1
  101. Online Learning: Beyond Regret stat.ML · 2010 · author #1
  102. Information-based complexity, feedback and dynamics in convex programming cs.IT · 2010 · author #2
  103. Online Learning via Sequential Complexities cs.LG · 2010 · author #1
  104. A Stochastic View of Optimal Regret through Minimax Duality cs.LG · 2009 · author #4

Mentions

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Frequent Coauthors