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Proceedings of Machine Learning Research

Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research
Proceedings of Machine Learning Research
PMLR · 2026-06-02 · via Proceedings of Machine Learning Research

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Volume 40: Conference on Learning Theory, 3-6 July 2015, Paris, France

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Editors: Peter Grünwald, Elad Hazan, Satyen Kale

[bib][citeproc]

Contents:

  • Preface
  • Regular Papers
  • Open Problems

Filter Authors: Filter Titles:

Preface

Conference on Learning Theory 2015: Preface

; Proceedings of The 28th Conference on Learning Theory, PMLR 40:1-3

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Regular Papers

Open Problems

Open Problem: Restricted Eigenvalue Condition for Heavy Tailed Designs

Arindam Banerjee, Sheng Chen, Vidyashankar Sivakumar; Proceedings of The 28th Conference on Learning Theory, PMLR 40:1752-1755

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Open Problem: The landscape of the loss surfaces of multilayer networks

Anna Choromanska, Yann LeCun, Gérard Ben Arous; Proceedings of The 28th Conference on Learning Theory, PMLR 40:1756-1760

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Open Problem: The Oracle Complexity of Smooth Convex Optimization in Nonstandard Settings

Cristóbal Guzmán; Proceedings of The 28th Conference on Learning Theory, PMLR 40:1761-1763

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Open Problem: Online Sabotaged Shortest Path

Wouter M. Koolen, Manfred K. Warmuth, Dmitri Adamskiy; Proceedings of The 28th Conference on Learning Theory, PMLR 40:1764-1766

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Open Problem: Learning Quantum Circuits with Queries

Jeremy Kun, Lev Reyzin; Proceedings of The 28th Conference on Learning Theory, PMLR 40:1767-1769

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Open Problem: Recursive Teaching Dimension Versus VC Dimension

Hans U. Simon, Sandra Zilles; Proceedings of The 28th Conference on Learning Theory, PMLR 40:1770-1772

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On Consistent Surrogate Risk Minimization and Property Elicitation

Arpit Agarwal, Shivani Agarwal; Proceedings of The 28th Conference on Learning Theory, PMLR 40:4-22

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Online Learning with Feedback Graphs: Beyond Bandits

Noga Alon, Nicolò Cesa-Bianchi, Ofer Dekel, Tomer Koren; Proceedings of The 28th Conference on Learning Theory, PMLR 40:23-35

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Learning Overcomplete Latent Variable Models through Tensor Methods

Animashree Anandkumar, Rong Ge, Majid Janzamin; Proceedings of The 28th Conference on Learning Theory, PMLR 40:36-112

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Simple, Efficient, and Neural Algorithms for Sparse Coding

Sanjeev Arora, Rong Ge, Tengyu Ma, Ankur Moitra; Proceedings of The 28th Conference on Learning Theory, PMLR 40:113-149

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Label optimal regret bounds for online local learning

Pranjal Awasthi, Moses Charikar, Kevin A Lai, Andrej Risteski; Proceedings of The 28th Conference on Learning Theory, PMLR 40:150-166

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Efficient Learning of Linear Separators under Bounded Noise

Pranjal Awasthi, Maria-Florina Balcan, Nika Haghtalab, Ruth Urner; Proceedings of The 28th Conference on Learning Theory, PMLR 40:167-190

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Efficient Representations for Lifelong Learning and Autoencoding

Maria-Florina Balcan, Avrim Blum, Santosh Vempala; Proceedings of The 28th Conference on Learning Theory, PMLR 40:191-210

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Optimally Combining Classifiers Using Unlabeled Data

Akshay Balsubramani, Yoav Freund; Proceedings of The 28th Conference on Learning Theory, PMLR 40:211-225

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Minimax Fixed-Design Linear Regression

Peter L. Bartlett, Wouter M. Koolen, Alan Malek, Eiji Takimoto, Manfred K. Warmuth; Proceedings of The 28th Conference on Learning Theory, PMLR 40:226-239

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Escaping the Local Minima via Simulated Annealing: Optimization of Approximately Convex Functions

Alexandre Belloni, Tengyuan Liang, Hariharan Narayanan, Alexander Rakhlin; Proceedings of The 28th Conference on Learning Theory, PMLR 40:240-265

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Bandit Convex Optimization: \sqrtT Regret in One Dimension

Sébastien Bubeck, Ofer Dekel, Tomer Koren, Yuval Peres; Proceedings of The 28th Conference on Learning Theory, PMLR 40:266-278

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The entropic barrier: a simple and optimal universal self-concordant barrier

Sébastien Bubeck, Ronen Eldan; Proceedings of The 28th Conference on Learning Theory, PMLR 40:279-279

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Optimum Statistical Estimation with Strategic Data Sources

Yang Cai, Constantinos Daskalakis, Christos Papadimitriou; Proceedings of The 28th Conference on Learning Theory, PMLR 40:280-296

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On the Complexity of Learning with Kernels

Nicolò Cesa-Bianchi, Yishay Mansour, Ohad Shamir; Proceedings of The 28th Conference on Learning Theory, PMLR 40:297-325

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Learnability of Solutions to Conjunctive Queries: The Full Dichotomy

Hubie Chen, Matthew Valeriote; Proceedings of The 28th Conference on Learning Theory, PMLR 40:326-337

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Sequential Information Maximization: When is Greedy Near-optimal?

Yuxin Chen, S. Hamed Hassani, Amin Karbasi, Andreas Krause; Proceedings of The 28th Conference on Learning Theory, PMLR 40:338-363

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Efficient Sampling for Gaussian Graphical Models via Spectral Sparsification

Dehua Cheng, Yu Cheng, Yan Liu, Richard Peng, Shang-Hua Teng; Proceedings of The 28th Conference on Learning Theory, PMLR 40:364-390

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Stochastic Block Model and Community Detection in Sparse Graphs: A spectral algorithm with optimal rate of recovery

Peter Chin, Anup Rao, Van Vu; Proceedings of The 28th Conference on Learning Theory, PMLR 40:391-423

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On-Line Learning Algorithms for Path Experts with Non-Additive Losses

Corinna Cortes, Vitaly Kuznetsov, Mehryar Mohri, Manfred Warmuth; Proceedings of The 28th Conference on Learning Theory, PMLR 40:424-447

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Truthful Linear Regression

Rachel Cummings, Stratis Ioannidis, Katrina Ligett; Proceedings of The 28th Conference on Learning Theory, PMLR 40:448-483

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A PTAS for Agnostically Learning Halfspaces

Amit Daniely; Proceedings of The 28th Conference on Learning Theory, PMLR 40:484-502

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S2: An Efficient Graph Based Active Learning Algorithm with Application to Nonparametric Classification

Gautam Dasarathy, Robert Nowak, Xiaojin Zhu; Proceedings of The 28th Conference on Learning Theory, PMLR 40:503-522

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Improved Sum-of-Squares Lower Bounds for Hidden Clique and Hidden Submatrix Problems

Yash Deshpande, Andrea Montanari; Proceedings of The 28th Conference on Learning Theory, PMLR 40:523-562

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Contextual Dueling Bandits

Miroslav Dudík, Katja Hofmann, Robert E. Schapire, Aleksandrs Slivkins, Masrour Zoghi; Proceedings of The 28th Conference on Learning Theory, PMLR 40:563-587

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Beyond Hartigan Consistency: Merge Distortion Metric for Hierarchical Clustering

Justin Eldridge, Mikhail Belkin, Yusu Wang; Proceedings of The 28th Conference on Learning Theory, PMLR 40:588-606

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Faster Algorithms for Testing under Conditional Sampling

Moein Falahatgar, Ashkan Jafarpour, Alon Orlitsky, Venkatadheeraj Pichapati, Ananda Theertha Suresh; Proceedings of The 28th Conference on Learning Theory, PMLR 40:607-636

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Learning and inference in the presence of corrupted inputs

Uriel Feige, Yishay Mansour, Robert Schapire; Proceedings of The 28th Conference on Learning Theory, PMLR 40:637-657

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From Averaging to Acceleration, There is Only a Step-size

Nicolas Flammarion, Francis Bach; Proceedings of The 28th Conference on Learning Theory, PMLR 40:658-695

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Variable Selection is Hard

Dean Foster, Howard Karloff, Justin Thaler; Proceedings of The 28th Conference on Learning Theory, PMLR 40:696-709

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Vector-Valued Property Elicitation

Rafael Frongillo, Ian A. Kash; Proceedings of The 28th Conference on Learning Theory, PMLR 40:710-727

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Competing with the Empirical Risk Minimizer in a Single Pass

Roy Frostig, Rong Ge, Sham M. Kakade, Aaron Sidford; Proceedings of The 28th Conference on Learning Theory, PMLR 40:728-763

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A Chaining Algorithm for Online Nonparametric Regression

Pierre Gaillard, Sébastien Gerchinovitz; Proceedings of The 28th Conference on Learning Theory, PMLR 40:764-796

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Escaping From Saddle Points — Online Stochastic Gradient for Tensor Decomposition

Rong Ge, Furong Huang, Chi Jin, Yang Yuan; Proceedings of The 28th Conference on Learning Theory, PMLR 40:797-842

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Learning the dependence structure of rare events: a non-asymptotic study

Nicolas Goix, Anne Sabourin, Stéphan Clémen\ccon; Proceedings of The 28th Conference on Learning Theory, PMLR 40:843-860

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Thompson Sampling for Learning Parameterized Markov Decision Processes

Aditya Gopalan, Shie Mannor; Proceedings of The 28th Conference on Learning Theory, PMLR 40:861-898

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Computational Lower Bounds for Community Detection on Random Graphs

Bruce Hajek, Yihong Wu, Jiaming Xu; Proceedings of The 28th Conference on Learning Theory, PMLR 40:899-928

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Adaptive Recovery of Signals by Convex Optimization

Zaid Harchaoui, Anatoli Juditsky, Arkadi Nemirovski, Dmitry Ostrovsky; Proceedings of The 28th Conference on Learning Theory, PMLR 40:929-955

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Tensor principal component analysis via sum-of-square proofs

Samuel B. Hopkins, Jonathan Shi, David Steurer; Proceedings of The 28th Conference on Learning Theory, PMLR 40:956-1006

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Fast Exact Matrix Completion with Finite Samples

Prateek Jain, Praneeth Netrapalli; Proceedings of The 28th Conference on Learning Theory, PMLR 40:1007-1034

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Exp-Concavity of Proper Composite Losses

Parameswaran Kamalaruban, Robert Williamson, Xinhua Zhang; Proceedings of The 28th Conference on Learning Theory, PMLR 40:1035-1065

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On Learning Distributions from their Samples

Sudeep Kamath, Alon Orlitsky, Dheeraj Pichapati, Ananda Theertha Suresh; Proceedings of The 28th Conference on Learning Theory, PMLR 40:1066-1100

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MCMC Learning

Varun Kanade, Elchanan Mossel; Proceedings of The 28th Conference on Learning Theory, PMLR 40:1101-1128

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Online PCA with Spectral Bounds

Zohar Karnin, Edo Liberty; Proceedings of The 28th Conference on Learning Theory, PMLR 40:1129-1140

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Regret Lower Bound and Optimal Algorithm in Dueling Bandit Problem

Junpei Komiyama, Junya Honda, Hisashi Kashima, Hiroshi Nakagawa; Proceedings of The 28th Conference on Learning Theory, PMLR 40:1141-1154

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Second-order Quantile Methods for Experts and Combinatorial Games

Wouter M. Koolen, Tim Van Erven; Proceedings of The 28th Conference on Learning Theory, PMLR 40:1155-1175

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Hierarchical Label Queries with Data-Dependent Partitions

Samory Kpotufe, Ruth Urner, Shai Ben-David; Proceedings of The 28th Conference on Learning Theory, PMLR 40:1176-1189

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Algorithms for Lipschitz Learning on Graphs

Rasmus Kyng, Anup Rao, Sushant Sachdeva, Daniel A. Spielman; Proceedings of The 28th Conference on Learning Theory, PMLR 40:1190-1223

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Low Rank Matrix Completion with Exponential Family Noise

Jean Lafond; Proceedings of The 28th Conference on Learning Theory, PMLR 40:1224-1243

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Bad Universal Priors and Notions of Optimality

Jan Leike, Marcus Hutter; Proceedings of The 28th Conference on Learning Theory, PMLR 40:1244-1259

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Learning with Square Loss: Localization through Offset Rademacher Complexity

Tengyuan Liang, Alexander Rakhlin, Karthik Sridharan; Proceedings of The 28th Conference on Learning Theory, PMLR 40:1260-1285

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Achieving All with No Parameters: AdaNormalHedge

Haipeng Luo, Robert E. Schapire; Proceedings of The 28th Conference on Learning Theory, PMLR 40:1286-1304

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Lower and Upper Bounds on the Generalization of Stochastic Exponentially Concave Optimization

Mehrdad Mahdavi, Lijun Zhang, Rong Jin; Proceedings of The 28th Conference on Learning Theory, PMLR 40:1305-1320

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Correlation Clustering with Noisy Partial Information

Konstantin Makarychev, Yury Makarychev, Aravindan Vijayaraghavan; Proceedings of The 28th Conference on Learning Theory, PMLR 40:1321-1342

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Online Density Estimation of Bradley-Terry Models

Issei Matsumoto, Kohei Hatano, Eiji Takimoto; Proceedings of The 28th Conference on Learning Theory, PMLR 40:1343-1359

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First-order regret bounds for combinatorial semi-bandits

Gergely Neu; Proceedings of The 28th Conference on Learning Theory, PMLR 40:1360-1375

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Norm-Based Capacity Control in Neural Networks

Behnam Neyshabur, Ryota Tomioka, Nathan Srebro; Proceedings of The 28th Conference on Learning Theory, PMLR 40:1376-1401

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Cortical Learning via Prediction

Christos H. Papadimitriou, Santosh S. Vempala; Proceedings of The 28th Conference on Learning Theory, PMLR 40:1402-1422

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Partitioning Well-Clustered Graphs: Spectral Clustering Works!

Richard Peng, He Sun, Luca Zanetti; Proceedings of The 28th Conference on Learning Theory, PMLR 40:1423-1455

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Batched Bandit Problems

Vianney Perchet, Philippe Rigollet, Sylvain Chassang, Erik Snowberg; Proceedings of The 28th Conference on Learning Theory, PMLR 40:1456-1456

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Hierarchies of Relaxations for Online Prediction Problems with Evolving Constraints

Alexander Rakhlin, Karthik Sridharan; Proceedings of The 28th Conference on Learning Theory, PMLR 40:1457-1479

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Fast Mixing for Discrete Point Processes

Patrick Rebeschini, Amin Karbasi; Proceedings of The 28th Conference on Learning Theory, PMLR 40:1480-1500

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Generalized Mixability via Entropic Duality

Mark D. Reid, Rafael M. Frongillo, Robert C. Williamson, Nishant Mehta; Proceedings of The 28th Conference on Learning Theory, PMLR 40:1501-1522

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On the Complexity of Bandit Linear Optimization

Ohad Shamir; Proceedings of The 28th Conference on Learning Theory, PMLR 40:1523-1551

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An Almost Optimal PAC Algorithm

Hans U. Simon; Proceedings of The 28th Conference on Learning Theory, PMLR 40:1552-1563

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Minimax rates for memory-bounded sparse linear regression

Jacob Steinhardt, John Duchi; Proceedings of The 28th Conference on Learning Theory, PMLR 40:1564-1587

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Interactive Fingerprinting Codes and the Hardness of Preventing False Discovery

Thomas Steinke, Jonathan Ullman; Proceedings of The 28th Conference on Learning Theory, PMLR 40:1588-1628

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Convex Risk Minimization and Conditional Probability Estimation

Matus Telgarsky, Miroslav Dudík, Robert Schapire; Proceedings of The 28th Conference on Learning Theory, PMLR 40:1629-1682

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Regularized Linear Regression: A Precise Analysis of the Estimation Error

Christos Thrampoulidis, Samet Oymak, Babak Hassibi; Proceedings of The 28th Conference on Learning Theory, PMLR 40:1683-1709

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Max vs Min: Tensor Decomposition and ICA with nearly Linear Sample Complexity

Santosh S. Vempala, Ying. Xiao; Proceedings of The 28th Conference on Learning Theory, PMLR 40:1710-1723

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On Convergence of Emphatic Temporal-Difference Learning

H. Yu; Proceedings of The 28th Conference on Learning Theory, PMLR 40:1724-1751

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