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Alexander Rakhlin

Identifiers

  • name variant Alexander Rakhlin 0.60 · backfill

Papers (71)

  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. Deep learning: a statistical viewpoint math.ST · 2021 · author #3
  9. On the Minimal Error of Empirical Risk Minimization math.ST · 2021 · author #2
  10. Top-$k$ eXtreme Contextual Bandits with Arm Hierarchy stat.ML · 2021 · author #2
  11. Learning the Linear Quadratic Regulator from Nonlinear Observations cs.LG · 2020 · author #7
  12. Instance-Dependent Complexity of Contextual Bandits and Reinforcement Learning: A Disagreement-Based Perspective cs.LG · 2020 · author #2
  13. Fast Mixing of Multi-Scale Langevin Dynamics under the Manifold Hypothesis stat.ML · 2020 · author #3
  14. On Suboptimality of Least Squares with Application to Estimation of Convex Bodies math.ST · 2020 · author #2
  15. Learning nonlinear dynamical systems from a single trajectory cs.LG · 2020 · author #2
  16. Beyond UCB: Optimal and Efficient Contextual Bandits with Regression Oracles cs.LG · 2020 · author #2
  17. $\ell_{\infty}$ Vector Contraction for Rademacher Complexity cs.LG · 2019 · author #2
  18. Data Driven Estimation of Stochastic Switched Linear Systems of Unknown Order eess.SY · 2019 · author #2
  19. On the Multiple Descent of Minimum-Norm Interpolants and Restricted Lower Isometry of Kernels math.ST · 2019 · author #2
  20. Breast Tumor Cellularity Assessment using Deep Neural Networks eess.IV · 2019 · author #1
  21. Optimality of Maximum Likelihood for Log-Concave Density Estimation and Bounded Convex Regression math.ST · 2019 · author #3
  22. Nonparametric Finite Time LTI System Identification eess.SY · 2019 · author #2
  23. Consistency of Interpolation with Laplace Kernels is a High-Dimensional Phenomenon stat.ML · 2018 · author #1
  24. Near optimal finite time identification of arbitrary linear dynamical systems cs.SY · 2018 · author #2
  25. Just Interpolate: Kernel "Ridgeless" Regression Can Generalize math.ST · 2018 · author #2
  26. Does data interpolation contradict statistical optimality? stat.ML · 2018 · author #2
  27. Angiodysplasia Detection and Localization Using Deep Convolutional Neural Networks cs.CV · 2018 · author #3
  28. Online Learning: Sufficient Statistics and the Burkholder Method cs.LG · 2018 · author #2
  29. Automatic Instrument Segmentation in Robot-Assisted Surgery Using Deep Learning cs.CV · 2018 · author #2
  30. Deep Convolutional Neural Networks for Breast Cancer Histology Image Analysis cs.CV · 2018 · author #1
  31. Theory of Deep Learning IIb: Optimization Properties of SGD cs.LG · 2018 · author #3
  32. Size-Independent Sample Complexity of Neural Networks cs.LG · 2017 · author #2
  33. Pediatric Bone Age Assessment Using Deep Convolutional Neural Networks cs.CV · 2017 · author #2
  34. Fisher-Rao Metric, Geometry, and Complexity of Neural Networks cs.LG · 2017 · author #3
  35. Weighted Message Passing and Minimum Energy Flow for Heterogeneous Stochastic Block Models with Side Information math.ST · 2017 · author #3
  36. ZigZag: A new approach to adaptive online learning cs.LG · 2017 · author #2
  37. Non-convex learning via Stochastic Gradient Langevin Dynamics: a nonasymptotic analysis cs.LG · 2017 · author #2
  38. A Tutorial on Online Supervised Learning with Applications to Node Classification in Social Networks cs.LG · 2016 · author #1
  39. On Detection and Structural Reconstruction of Small-World Random Networks math.ST · 2016 · author #3
  40. Inference via Message Passing on Partially Labeled Stochastic Block Models math.ST · 2016 · author #3
  41. Distributed Estimation of Dynamic Parameters : Regret Analysis math.OC · 2016 · author #2
  42. BISTRO: An Efficient Relaxation-Based Method for Contextual Bandits cs.LG · 2016 · author #1
  43. Finite-time Analysis of the Distributed Detection Problem cs.SY · 2015 · author #2
  44. On Equivalence of Martingale Tail Bounds and Deterministic Regret Inequalities math.PR · 2015 · author #1
  45. Adaptive Online Learning cs.LG · 2015 · author #2
  46. Hierarchies of Relaxations for Online Prediction Problems with Evolving Constraints cs.LG · 2015 · author #1
  47. Learning with Square Loss: Localization through Offset Rademacher Complexity stat.ML · 2015 · author #2
  48. Computational and Statistical Boundaries for Submatrix Localization in a Large Noisy Matrix math.ST · 2015 · author #3
  49. Sequential Probability Assignment with Binary Alphabets and Large Classes of Experts cs.IT · 2015 · author #1
  50. Escaping the Local Minima via Simulated Annealing: Optimization of Approximately Convex Functions math.NA · 2015 · author #4
  51. Online Nonparametric Regression with General Loss Functions stat.ML · 2015 · author #1
  52. Online Optimization : Competing with Dynamic Comparators cs.LG · 2015 · author #2
  53. Distributed Detection : Finite-time Analysis and Impact of Network Topology math.OC · 2014 · author #2
  54. Geometric Inference for General High-Dimensional Linear Inverse Problems math.ST · 2014 · author #3
  55. On Zeroth-Order Stochastic Convex Optimization via Random Walks cs.LG · 2014 · author #3
  56. Online Nonparametric Regression stat.ML · 2014 · author #1
  57. Optimization, Learning, and Games with Predictable Sequences cs.LG · 2013 · author #1
  58. Online Learning of Dynamic Parameters in Social Networks math.OC · 2013 · author #2
  59. Efficient Sampling from Time-Varying Log-Concave Distributions stat.ML · 2013 · author #2
  60. Empirical entropy, minimax regret and minimax risk math.ST · 2013 · author #1
  61. Competing With Strategies stat.ML · 2013 · author #2
  62. Online Learning with Predictable Sequences stat.ML · 2012 · author #1
  63. Relax and Localize: From Value to Algorithms cs.LG · 2012 · author #1
  64. Making Gradient Descent Optimal for Strongly Convex Stochastic Optimization cs.LG · 2011 · author #1
  65. No Internal Regret via Neighborhood Watch cs.LG · 2011 · author #2
  66. Stochastic convex optimization with bandit feedback math.OC · 2011 · author #5
  67. Online Learning: Stochastic and Constrained Adversaries stat.ML · 2011 · author #1
  68. Online Learning: Beyond Regret stat.ML · 2010 · author #1
  69. Information-based complexity, feedback and dynamics in convex programming cs.IT · 2010 · author #2
  70. Online Learning via Sequential Complexities cs.LG · 2010 · author #1
  71. A Stochastic View of Optimal Regret through Minimax Duality cs.LG · 2009 · author #4

Mentions

  • 2103.09177 #3 · arxiv_oai · confidence 0.70 Alexander Rakhlin
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Frequent Coauthors