Papers
A simple multi-armed bandit algorithm with optimal variation-bounded regret
Elad Hazan, Satyen Kale
Bounds on Individual Risk for Log-loss Predictors
Peter D. Grünwald, Wojciech Kotłowski
Does an Efficient Calibrated Forecasting Strategy Exist?
Jacob Abernethy, Shie Mannor
Identifiability of Priors from Bounded Sample Sizes with Applications to Transfer Learning
Liu Yang, Steve Hanneke, Jaime Carbonell
The Sample Complexity of Dictionary Learning
Daniel Vainsencher, Shie Mannor, Alfred M. Bruckstein
Agnostic KWIK learning and efficient approximate reinforcement learning
István Szita, Csaba Szepesvári
Adaptive Density Level Set Clustering
Ingo Steinwart
Contextual Bandits with Similarity Information
Aleksandrs Slivkins
Collaborative Filtering with the Trace Norm: Learning, Bounding, and Transducing
Ohad Shamir, Shai Shalev-Shwartz
Optimal aggregation of affine estimators
Joseph Salmon, Arnak Dalalyan
Sequential Event Prediction with Association Rules
Cynthia Rudin, Benjamin Letham, Ansaf Salleb-Aouissi et al.
Neyman-Pearson classification under a strict constraint
Philippe Rigollet, Xin Tong
Online Learning: Beyond Regret
Alexander Rakhlin, Karthik Sridharan, Ambuj Tewari
The Rate of Convergence of Adaboost
Indraneel Mukherjee, Cynthia Rudin, Robert E. Schapire
Robust approachability and regret minimization in games with partial monitoring
Shie Mannor, Vianney Perchet, Gilles Stoltz
A Finite-Time Analysis of Multi-armed Bandits Problems with Kullback-Leibler Divergences
Odalric-Ambrym Maillard, Rémi Munos, Gilles Stoltz
Maximum Likelihood vs. Sequential Normalized Maximum Likelihood in On-line Density Estimation
Wojciech Kotłowski, Peter Grünwald
A Close Look to Margin Complexity and Related Parameters
Michael Kallweit, Hans Ulrich Simon
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
On the Consistency of Multi-Label Learning
Wei Gao, Zhi-Hua Zhou
Concentration-Based Guarantees for Low-Rank Matrix Reconstruction
Rina Foygel, Nathan Srebro