Algorithmic Learning Theory 2019: Preface

Aurélien Garivier, Satyen Kale; Proceedings of the 30th International Conference on Algorithmic Learning Theory, PMLR 98:1-2

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On Learning Graphs with Edge-Detecting Queries

Hasan Abasi, Bshouty Nader; Proceedings of the 30th International Conference on Algorithmic Learning Theory, PMLR 98:3-30

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An Exponential Efron-Stein Inequality for $L_q$ Stable Learning Rules

Karim Abou-Moustafa, Csaba Szepesvári; Proceedings of the 30th International Conference on Algorithmic Learning Theory, PMLR 98:31-63

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Dimensionality Reduction and (Bucket) Ranking: a Mass Transportation Approach

Mastane Achab, Anna Korba, Stephan Clémençon; Proceedings of the 30th International Conference on Algorithmic Learning Theory, PMLR 98:64-93

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A minimax near-optimal algorithm for adaptive rejection sampling

Juliette Achddou, Joseph Lam-Weil, Alexandra Carpentier, Gilles Blanchard; Proceedings of the 30th International Conference on Algorithmic Learning Theory, PMLR 98:94-126

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Attribute-efficient learning of monomials over highly-correlated variables

Alexandr Andoni, Rishabh Dudeja, Daniel Hsu, Kiran Vodrahalli; Proceedings of the 30th International Conference on Algorithmic Learning Theory, PMLR 98:127-161

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Improved Generalization Bounds for Robust Learning

Idan Attias, Aryeh Kontorovich, Yishay Mansour; Proceedings of the 30th International Conference on Algorithmic Learning Theory, PMLR 98:162-183

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A simple parameter-free and adaptive approach to optimization under a minimal local smoothness assumption

Peter L. Bartlett, Victor Gabillon, Michal Valko; Proceedings of the 30th International Conference on Algorithmic Learning Theory, PMLR 98:184-206

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Adaptive Exact Learning of Decision Trees from Membership Queries

Nader H. Bshouty, Catherine A. Haddad-Zaknoon; Proceedings of the 30th International Conference on Algorithmic Learning Theory, PMLR 98:207-234

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Generalize Across Tasks: Efficient Algorithms for Linear Representation Learning

Brian Bullins, Elad Hazan, Adam Kalai, Roi Livni; Proceedings of the 30th International Conference on Algorithmic Learning Theory, PMLR 98:235-246

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Dynamic Pricing with Finitely Many Unknown Valuations

Nicolò Cesa-Bianchi, Tommaso Cesari, Vianney Perchet; Proceedings of the 30th International Conference on Algorithmic Learning Theory, PMLR 98:247-273

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Online Non-Additive Path Learning under Full and Partial Information

Corinna Cortes, Vitaly Kuznetsov, Mehryar Mohri, Holakou Rahmanian, Manfred Warmuth; Proceedings of the 30th International Conference on Algorithmic Learning Theory, PMLR 98:274-299

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Two-Player Games for Efficient Non-Convex Constrained Optimization

Andrew Cotter, Heinrich Jiang, Karthik Sridharan; Proceedings of the 30th International Conference on Algorithmic Learning Theory, PMLR 98:300-332

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Competitive ratio vs regret minimization: achieving the best of both worlds

Amit Daniely, Yishay Mansour; Proceedings of the 30th International Conference on Algorithmic Learning Theory, PMLR 98:333-368

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Hardness of Improper One-Sided Learning of Conjunctions For All Uniformly Falsifiable CSPs

Alexander Durgin, Brendan Juba; Proceedings of the 30th International Conference on Algorithmic Learning Theory, PMLR 98:369-382

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Limit Learning Equivalence Structures

Ekaterina Fokina, Timo Kötzing, Luca San Mauro; Proceedings of the 30th International Conference on Algorithmic Learning Theory, PMLR 98:383-403

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Uniform regret bounds over $\mathbb{R}^d$ for the sequential linear regression problem with the square loss

Pierre Gaillard, Sébastien Gerchinovitz, Malo Huard, Gilles Stoltz; Proceedings of the 30th International Conference on Algorithmic Learning Theory, PMLR 98:404-432

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A tight excess risk bound via a unified PAC-Bayesian–Rademacher–Shtarkov–MDL complexity

Peter D. Grünwald, Nishant A. Mehta; Proceedings of the 30th International Conference on Algorithmic Learning Theory, PMLR 98:433-465

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Sample Compression for Real-Valued Learners

Steve Hanneke, Aryeh Kontorovich, Menachem Sadigurschi; Proceedings of the 30th International Conference on Algorithmic Learning Theory, PMLR 98:466-488

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A Sharp Lower Bound for Agnostic Learning with Sample Compression Schemes

Steve Hanneke, Aryeh Kontorovich; Proceedings of the 30th International Conference on Algorithmic Learning Theory, PMLR 98:489-505

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Optimal Collusion-Free Teaching

David Kirkpatrick, Hans U. Simon, Sandra Zilles; Proceedings of the 30th International Conference on Algorithmic Learning Theory, PMLR 98:506-528

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Cleaning up the neighborhood: A full classification for adversarial partial monitoring

Tor Lattimore, Csaba Szepesvári; Proceedings of the 30th International Conference on Algorithmic Learning Theory, PMLR 98:529-556

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Online Influence Maximization with Local Observations

Gábor Lugosi, Gergely Neu, Julia Olkhovskaya; Proceedings of the 30th International Conference on Algorithmic Learning Theory, PMLR 98:557-580

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Can Adversarially Robust Learning LeverageComputational Hardness?

Saeed Mahloujifar, Mohammad Mahmoody; Proceedings of the 30th International Conference on Algorithmic Learning Theory, PMLR 98:581-609

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Sequential change-point detection: Laplace concentration of scan statistics and non-asymptotic delay bounds

Odalric-Ambrym Maillard; Proceedings of the 30th International Conference on Algorithmic Learning Theory, PMLR 98:610-632

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Average-Case Information Complexity of Learning

Ido Nachum, Amir Yehudayoff; Proceedings of the 30th International Conference on Algorithmic Learning Theory, PMLR 98:633-646

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Interplay of minimax estimation and minimax support recovery under sparsity

Mohamed Ndaoud; Proceedings of the 30th International Conference on Algorithmic Learning Theory, PMLR 98:647-668

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Ising Models with Latent Conditional Gaussian Variables

Frank Nussbaum, Joachim Giesen; Proceedings of the 30th International Conference on Algorithmic Learning Theory, PMLR 98:669-681

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Exploiting geometric structure in mixture proportion estimation with generalised Blanchard-Lee-Scott estimators

Henry Reeve, Ata Kabán; Proceedings of the 30th International Conference on Algorithmic Learning Theory, PMLR 98:682-699

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PAC Battling Bandits in the Plackett-Luce Model

Aadirupa Saha, Aditya Gopalan; Proceedings of the 30th International Conference on Algorithmic Learning Theory, PMLR 98:700-737

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A Generalized Neyman-Pearson Criterion for Optimal Domain Adaptation

Clayton Scott; Proceedings of the 30th International Conference on Algorithmic Learning Theory, PMLR 98:738-761

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General parallel optimization a without metric

Xuedong Shang, Emilie Kaufmann, Michal Valko; Proceedings of the 30th International Conference on Algorithmic Learning Theory, PMLR 98:762-788

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Old Techniques in Differentially Private Linear Regression

Or Sheffet; Proceedings of the 30th International Conference on Algorithmic Learning Theory, PMLR 98:789-827

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PeerReview4All: Fair and Accurate Reviewer Assignment in Peer Review

Ivan Stelmakh, Nihar B. Shah, Aarti Singh; Proceedings of the 30th International Conference on Algorithmic Learning Theory, PMLR 98:828-856

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Stochastic Nonconvex Optimization with Large Minibatches

Weiran Wang, Nathan Srebro; Proceedings of the 30th International Conference on Algorithmic Learning Theory, PMLR 98:857-882

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Online Linear Optimization with Sparsity Constraints

Jun-Kun Wang, Chi-Jen Lu, Shou-De Lin; Proceedings of the 30th International Conference on Algorithmic Learning Theory, PMLR 98:883-897

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Noninteractive Locally Private Learning of Linear Models via Polynomial Approximations

Di Wang, Adam Smith, Jinhui Xu; Proceedings of the 30th International Conference on Algorithmic Learning Theory, PMLR 98:898-903

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Minimax Learning of Ergodic Markov Chains

Geoffrey Wolfer, Aryeh Kontorovich; Proceedings of the 30th International Conference on Algorithmic Learning Theory, PMLR 98:904-930

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