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Volume 99: Conference on Learning Theory, 25-28 June 2019, Phoenix, USA
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Editors: Alina Beygelzimer, Daniel Hsu
Preface
Conference on Learning Theory 2019: Preface
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:1-2
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Contributed Papers
Inference under Information Constraints: Lower Bounds from Chi-Square Contraction
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:3-17
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Learning in Non-convex Games with an Optimization Oracle
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:18-29
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Learning to Prune: Speeding up Repeated Computations
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:30-33
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Towards Testing Monotonicity of Distributions Over General Posets
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:34-82
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Testing Mixtures of Discrete Distributions
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:83-114
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Normal Approximation for Stochastic Gradient Descent via Non-Asymptotic Rates of Martingale CLT
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:115-137
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Adaptively Tracking the Best Bandit Arm with an Unknown Number of Distribution Changes
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:138-158
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Achieving Optimal Dynamic Regret for Non-stationary Bandits without Prior Information
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:159-163
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A Universal Algorithm for Variational Inequalities Adaptive to Smoothness and Noise
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:164-194
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Learning Two Layer Rectified Neural Networks in Polynomial Time
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:195-268
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Private Center Points and Learning of Halfspaces
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:269-282
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Lower bounds for testing graphical models: colorings and antiferromagnetic Ising models
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:283-298
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Approximate Guarantees for Dictionary Learning
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:299-317
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The Optimal Approximation Factor in Density Estimation
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:318-341
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Sorted Top-k in Rounds
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:342-382
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Multi-armed Bandit Problems with Strategic Arms
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:383-416
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Universality of Computational Lower Bounds for Submatrix Detection
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:417-468
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Optimal Average-Case Reductions to Sparse PCA: From Weak Assumptions to Strong Hardness
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:469-470
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Learning rates for Gaussian mixtures under group action
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:471-491
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Near-optimal method for highly smooth convex optimization
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:492-507
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Improved Path-length Regret Bounds for Bandits
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:508-528
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Optimal Learning of Mallows Block Model
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:529-532
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Gaussian Process Optimization with Adaptive Sketching: Scalable and No Regret
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:533-557
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Disagreement-Based Combinatorial Pure Exploration: Sample Complexity Bounds and an Efficient Algorithm
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:558-588
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A Rank-1 Sketch for Matrix Multiplicative Weights
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:589-623
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On the Computational Power of Online Gradient Descent
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:624-662
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Active Regression via Linear-Sample Sparsification
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:663-695
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A New Algorithm for Non-stationary Contextual Bandits: Efficient, Optimal and Parameter-free
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:696-726
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Faster Algorithms for High-Dimensional Robust Covariance Estimation
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:727-757
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Testing Symmetric Markov Chains Without Hitting
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:758-785
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Fast Mean Estimation with Sub-Gaussian Rates
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:786-806
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Vortices Instead of Equilibria in MinMax Optimization: Chaos and Butterfly Effects of Online Learning in Zero-Sum Games
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:807-834
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Pure entropic regularization for metrical task systems
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:835-848
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A near-optimal algorithm for approximating the John Ellipsoid
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:849-873
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Artificial Constraints and Hints for Unbounded Online Learning
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:874-894
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Combining Online Learning Guarantees
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:895-913
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Learning from Weakly Dependent Data under Dobrushin’s Condition
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:914-928
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Space lower bounds for linear prediction in the streaming model
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:929-954
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Computationally and Statistically Efficient Truncated Regression
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:955-960
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Reconstructing Trees from Traces
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:961-978
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Is your function low dimensional?
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:979-993
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Computational Limitations in Robust Classification and Win-Win Results
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:994-1028
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Fast determinantal point processes via distortion-free intermediate sampling
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:1029-1049
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Minimax experimental design: Bridging the gap between statistical and worst-case approaches to least squares regression
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:1050-1069
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Communication and Memory Efficient Testing of Discrete Distributions
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:1070-1106
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Testing Identity of Multidimensional Histograms
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:1107-1131
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Lower Bounds for Parallel and Randomized Convex Optimization
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:1132-1157
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On the Performance of Thompson Sampling on Logistic Bandits
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:1158-1160
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Lower Bounds for Locally Private Estimation via Communication Complexity
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:1161-1191
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Sharp Analysis for Nonconvex SGD Escaping from Saddle Points
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:1192-1234
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Achieving the Bayes Error Rate in Stochastic Block Model by SDP, Robustly
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:1235-1269
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High probability generalization bounds for uniformly stable algorithms with nearly optimal rate
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:1270-1279
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Sum-of-squares meets square loss: Fast rates for agnostic tensor completion
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:1280-1318
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The Complexity of Making the Gradient Small in Stochastic Convex Optimization
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:1319-1345
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Statistical Learning with a Nuisance Component
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:1346-1348
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On the Regret Minimization of Nonconvex Online Gradient Ascent for Online PCA
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:1349-1373
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Optimal Tensor Methods in Smooth Convex and Uniformly ConvexOptimization
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:1374-1391
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Near Optimal Methods for Minimizing Convex Functions with Lipschitz $p$-th Derivatives
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:1392-1393
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Stabilized SVRG: Simple Variance Reduction for Nonconvex Optimization
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:1394-1448
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Learning Ising Models with Independent Failures
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:1449-1469
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Learning Neural Networks with Two Nonlinear Layers in Polynomial Time
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:1470-1499
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When can unlabeled data improve the learning rate?
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:1500-1518
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Sampling and Optimization on Convex Sets in Riemannian Manifolds of Non-Negative Curvature
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:1519-1561
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Better Algorithms for Stochastic Bandits with Adversarial Corruptions
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:1562-1578
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Tight analyses for non-smooth stochastic gradient descent
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:1579-1613
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Reasoning in Bayesian Opinion Exchange Networks Is PSPACE-Hard
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:1614-1648
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How Hard is Robust Mean Estimation?
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:1649-1682
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A Robust Spectral Algorithm for Overcomplete Tensor Decomposition
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:1683-1722
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Sample-Optimal Low-Rank Approximation of Distance Matrices
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:1723-1751
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Making the Last Iterate of SGD Information Theoretically Optimal
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:1752-1755
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Accuracy-Memory Tradeoffs and Phase Transitions in Belief Propagation
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:1756-1771
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The implicit bias of gradient descent on nonseparable data
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:1772-1798
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An Optimal High-Order Tensor Method for Convex Optimization
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:1799-1801
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Parameter-Free Online Convex Optimization with Sub-Exponential Noise
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:1802-1823
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Sample complexity of partition identification using multi-armed bandits
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:1824-1852
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Privately Learning High-Dimensional Distributions
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:1853-1902
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On Communication Complexity of Classification Problems
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:1903-1943
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Non-asymptotic Analysis of Biased Stochastic Approximation Scheme
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:1944-1974
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Discrepancy, Coresets, and Sketches in Machine Learning
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:1975-1993
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Bandit Principal Component Analysis
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:1994-2024
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Contextual bandits with continuous actions: Smoothing, zooming, and adapting
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:2025-2027
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Distribution-Dependent Analysis of Gibbs-ERM Principle
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:2028-2054
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Global Convergence of the EM Algorithm for Mixtures of Two Component Linear Regression
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:2055-2110
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An Information-Theoretic Approach to Minimax Regret in Partial Monitoring
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:2111-2139
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Solving Empirical Risk Minimization in the Current Matrix Multiplication Time
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:2140-2157
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On Mean Estimation for General Norms with Statistical Queries
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:2158-2172
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Nearly Minimax-Optimal Regret for Linearly Parameterized Bandits
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:2173-2174
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Sharp Theoretical Analysis for Nonparametric Testing under Random Projection
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:2175-2209
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Combinatorial Algorithms for Optimal Design
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:2210-2258
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Nonconvex sampling with the Metropolis-adjusted Langevin algorithm
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:2259-2293
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Beyond Least-Squares: Fast Rates for Regularized Empirical Risk Minimization through Self-Concordance
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:2294-2340
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Planting trees in graphs, and finding them back
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:2341-2371
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Uniform concentration and symmetrization for weak interactions
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:2372-2387
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Mean-field theory of two-layers neural networks: dimension-free bounds and kernel limit
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:2388-2464
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Batch-Size Independent Regret Bounds for the Combinatorial Multi-Armed Bandit Problem
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:2465-2489
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Lipschitz Adaptivity with Multiple Learning Rates in Online Learning
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:2490-2511
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VC Classes are Adversarially Robustly Learnable, but Only Improperly
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:2512-2530
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Affine Invariant Covariance Estimation for Heavy-Tailed Distributions
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:2531-2550
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Stochastic Gradient Descent Learns State Equations with Nonlinear Activations
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:2551-2579
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A Theory of Selective Prediction
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:2580-2594
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Consistency of Interpolation with Laplace Kernels is a High-Dimensional Phenomenon
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:2595-2623
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Classification with unknown class-conditional label noise on non-compact feature spaces
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:2624-2651
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The All-or-Nothing Phenomenon in Sparse Linear Regression
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:2652-2663
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Depth Separations in Neural Networks: What is Actually Being Separated?
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:2664-2666
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How do infinite width bounded norm networks look in function space?
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:2667-2690
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Exponential Convergence Time of Gradient Descent for One-Dimensional Deep Linear Neural Networks
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:2691-2713
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Learning Linear Dynamical Systems with Semi-Parametric Least Squares
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:2714-2802
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Finite-Time Error Bounds For Linear Stochastic Approximation andTD Learning
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:2803-2830
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Robustness of Spectral Methods for Community Detection
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:2831-2860
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Maximum Entropy Distributions: Bit Complexity and Stability
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:2861-2891
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Adaptive Hard Thresholding for Near-optimal Consistent Robust Regression
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:2892-2897
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Model-based RL in Contextual Decision Processes: PAC bounds and Exponential Improvements over Model-free Approaches
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:2898-2933
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Stochastic first-order methods: non-asymptotic and computer-aided analyses via potential functions
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:2934-2992
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The Relative Complexity of Maximum Likelihood Estimation, MAP Estimation, and Sampling
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:2993-3035
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The Gap Between Model-Based and Model-Free Methods on the Linear Quadratic Regulator: An Asymptotic Viewpoint
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:3036-3083
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Theoretical guarantees for sampling and inference in generative models with latent diffusions
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:3084-3114
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Gradient Descent for One-Hidden-Layer Neural Networks: Polynomial Convergence and SQ Lower Bounds
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:3115-3117
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Estimation of smooth densities in Wasserstein distance
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:3118-3119
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Estimating the Mixing Time of Ergodic Markov Chains
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:3120-3159
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Stochastic Approximation of Smooth and Strongly Convex Functions: Beyond the $O(1/T)$ Convergence Rate
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:3160-3179
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Open Problems
Open Problem: Is Margin Sufficient for Non-Interactive Private Distributed Learning?
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:3180-3184
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Open Problem: How fast can a multiclass test set be overfit?
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:3185-3189
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Open Problem: Do Good Algorithms Necessarily Query Bad Points?
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:3190-3193
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Open Problem: Risk of Ruin in Multiarmed Bandits
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:3194-3197
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Open Problem: Monotonicity of Learning
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:3198-3201
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Open Problem: The Oracle Complexity of Convex Optimization with Limited Memory
; Proceedings of the Thirty-Second Conference on Learning Theory, PMLR 99:3202-3210
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