Papers
1,396 papers found
Minimax Policies for Combinatorial Prediction Games
Jean-Yves Audibert, Sébastien Bubeck, Gábor Lugosi
Minimax Regret of Finite Partial-Monitoring Games in Stochastic Environments
Gábor Bartók, Dávid Pál, Csaba Szepesvári
Missing Information Impediments to Learnability
Loizos Michael
Mixability is Bayes Risk Curvature Relative to Log Loss
Tim Erven, Mark D. Reid, Robert C. Williamson
Monotone multi-armed bandit allocations
Aleksandrs Slivkins
Multiclass Learnability and the ERM principle
Amit Daniely, Sivan Sabato, Shai Ben-David et al.
Neyman-Pearson classification under a strict constraint
Philippe Rigollet, Xin Tong
Online Learning: Beyond Regret
Alexander Rakhlin, Karthik Sridharan, Ambuj Tewari
On the Consistency of Multi-Label Learning
Wei Gao, Zhi-Hua Zhou
Optimal aggregation of affine estimators
Joseph Salmon, Arnak Dalalyan
Oracle inequalities for computationally budgeted model selection
Alekh Agarwal, John C. Duchi, Peter L. Bartlett et al.
Regret Bounds for the Adaptive Control of Linear Quadratic Systems
Yasin Abbasi-Yadkori, Csaba Szepesvári
Robust approachability and regret minimization in games with partial monitoring
Shie Mannor, Vianney Perchet, Gilles Stoltz
Sample Complexity Bounds for Differentially Private Learning
Kamalika Chaudhuri, Daniel Hsu
Sequential Event Prediction with Association Rules
Cynthia Rudin, Benjamin Letham, Ansaf Salleb-Aouissi et al.
Sparsity Regret Bounds for Individual Sequences in Online Linear Regression
Sébastien Gerchinovitz
The KL-UCB Algorithm for Bounded Stochastic Bandits and Beyond
Aurélien Garivier, Olivier Cappé
The Rate of Convergence of Adaboost
Indraneel Mukherjee, Cynthia Rudin, Robert E. Schapire
The Sample Complexity of Dictionary Learning
Daniel Vainsencher, Shie Mannor, Alfred M. Bruckstein
Tight conditions for consistent variable selection in high dimensional nonparametric regression
Laëtitia Comminges, Arnak S. Dalalyan