Papers
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 et al.
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 et al.
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 et al.
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 et al.
A minimax near-optimal algorithm for adaptive rejection sampling
Juliette Achddou, Joseph Lam-Weil, Alexandra Carpentier et al.
Dimensionality Reduction and (Bucket) Ranking: a Mass Transportation Approach
Mastane Achab, Anna Korba, Stephan 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
Data-Driven Approach to Multiple-Source Domain Adaptation
Petar Stojanov, Mingming Gong, Jaime Carbonell et al.
Towards Gradient Free and Projection Free Stochastic Optimization
Anit Kumar Sahu, Manzil Zaheer, Soummya Kar
Evaluating model calibration in classification
Juozas Vaicenavicius, David Widmann, Carl Andersson et al.
Low-Dimensional Density Ratio Estimation for Covariate Shift Correction
Petar Stojanov, Mingming Gong, Jaime Carbonell et al.
Adaptive Minimax Regret against Smooth Logarithmic Losses over High-Dimensional l1-Balls via Envelope Complexity
Kohei Miyaguchi, Kenji Yamanishi
Structured Neural Topic Models for Reviews
Babak Esmaeili, Hongyi Huang, Byron Wallace et al.