ALT 2019

38 papers

Minimax Learning of Ergodic Markov Chains

Geoﬀrey Wolfer, Aryeh Kontorovich

Noninteractive Locally Private Learning of Linear Models via Polynomial Approximations

Di Wang, Adam Smith, Jinhui Xu

Online Linear Optimization with Sparsity Constraints

Jun-Kun Wang, Chi-Jen Lu, Shou-De Lin

Stochastic Nonconvex Optimization with Large Minibatches

Weiran Wang, Nathan Srebro

PeerReview4All: Fair and Accurate Reviewer Assignment in Peer Review

Ivan Stelmakh, Nihar B. Shah, Aarti Singh

Old Techniques in Differentially Private Linear Regression

Or Sheffet

General parallel optimization a without metric

Xuedong Shang, Emilie Kaufmann, Michal Valko

A Generalized Neyman-Pearson Criterion for Optimal Domain Adaptation

Clayton Scott

PAC Battling Bandits in the Plackett-Luce Model

Aadirupa Saha, Aditya Gopalan

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

Henry Reeve, Ata Kaban

Ising Models with Latent Conditional Gaussian Variables

Frank Nussbaum, Joachim Giesen

Interplay of minimax estimation and minimax support recovery under sparsity

Mohamed Ndaoud

Average-Case Information Complexity of Learning

Ido Nachum, Amir Yehudayoff

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

Odalric-ambrym Maillard

Can Adversarially Robust Learning LeverageComputational Hardness?

Saeed Mahloujifar, Mohammad Mahmoody

Online Influence Maximization with Local Observations

Gabor Lugosi, Gergely Neu, Julia Olkhovskaya

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

Tor Lattimore, Csaba Szepesvári

Optimal Collusion-Free Teaching

David Kirkpatrick, Hans U. Simon, Sandra Zilles

A Sharp Lower Bound for Agnostic Learning with Sample Compression Schemes

Steve Hanneke, Aryeh Kontorovich

Sample Compression for Real-Valued Learners

Steve Hanneke, Aryeh Kontorovich, Menachem Sadigurschi

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

Peter D. Grünwald, Nishant A. Mehta

Uniform regret bounds over R^d for the sequential linear regression problem with the square loss

Pierre Gaillard, Sébastien Gerchinovitz, Malo Huard, Gilles Stoltz

Limit Learning Equivalence Structures

Ekaterina Fokina, Timo Kötzing, Luca San Mauro

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

Alexander Durgin, Brendan Juba

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

Amit Daniely, Yishay Mansour

Two-Player Games for Efficient Non-Convex Constrained Optimization

Andrew Cotter, Heinrich Jiang, Karthik Sridharan

Online Non-Additive Path Learning under Full and Partial Information

Corinna Cortes, Vitaly Kuznetsov, Mehryar Mohri, Holakou Rahmanian, Manfred Warmuth

Dynamic Pricing with Finitely Many Unknown Valuations

Nicolò Cesa-bianchi, Tommaso Cesari, Vianney Perchet

Generalize Across Tasks: Efficient Algorithms for Linear Representation Learning

Brian Bullins, Elad Hazan, Adam Kalai, Roi Livni

Adaptive Exact Learning of Decision Trees from Membership Queries

Nader H. Bshouty, Catherine A. Haddad-Zaknoon

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

Peter L. Bartlett, Victor Gabillon, Michal Valko

Improved Generalization Bounds for Robust Learning

Idan Attias, Aryeh Kontorovich, Yishay Mansour

Attribute-efficient learning of monomials over highly-correlated variables

Alexandr Andoni, Rishabh Dudeja, Daniel Hsu, Kiran Vodrahalli

A minimax near-optimal algorithm for adaptive rejection sampling

Juliette Achddou, Joseph Lam-Weil, Alexandra Carpentier, Gilles Blanchard

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

Mastane Achab, Anna Korba, Stéphan Clémençon

An Exponential Efron-Stein Inequality for L_q Stable Learning Rules

Karim Abou-Moustafa, Csaba Szepesvári

On Learning Graphs with Edge-Detecting Queries

Hasan Abasi, Bshouty Nader

Algorithmic Learning Theory 2019: Preface

Aurélien Garivier, Satyen Kale