COLT 2011

42 papers

Monotone multi-armed bandit allocations

Aleksandrs Slivkins

Missing Information Impediments to Learnability

Loizos Michael

Minimax Algorithm for Learning Rotations

Wojciech Kotłowski, Manfred K. Warmuth

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, Eugene Kogan, David Madigan

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

A New Algorithm for Compressed Counting with Applications in Shannon Entropy Estimation in Dynamic Data

Ping Li, Cun-hui Zhang

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

Beyond the regret minimization barrier: an optimal algorithm for stochastic strongly-convex optimization

Elad Hazan, Satyen Kale

Safe Learning: bridging the gap between Bayes, MDL and statistical learning theory via empirical convexity

Peter Grünwald

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 Cappe

On the Consistency of Multi-Label Learning

Wei Gao, Zhi-Hua Zhou

Concentration-Based Guarantees for Low-Rank Matrix Reconstruction

Rina Foygel, Nathan Srebro

Complexity-Based Approach to Calibration with Checking Rules

Dean P. Foster, Alexander Rakhlin, Karthik Sridharan, Ambuj Tewari

Lower Bounds and Hardness Amplification for Learning Shallow Monotone Formulas

Vitaly Feldman, Homin K. Lee, Rocco A. Servedio

Distribution-Independent Evolvability of Linear Threshold Functions

Vitaly Feldman

Mixability is Bayes Risk Curvature Relative to Log Loss

Tim Erven, Mark D. Reid, Robert C. Williamson

Multiclass Learnability and the ERM principle

Amit Daniely, Sivan Sabato, Shai Ben-David, Shai Shalev-shwartz

Tight conditions for consistent variable selection in high dimensional nonparametric regression

Laëtitia Comminges, Arnak S. Dalalyan

Sample Complexity Bounds for Differentially Private Learning

Kamalika Chaudhuri, Daniel Hsu

Minimax Regret of Finite Partial-Monitoring Games in Stochastic Environments

Gabor Bartok, Dávid Pál, Csaba Szepesvári

Minimax Policies for Combinatorial Prediction Games

Jean-yves Audibert, Sébastien Bubeck, Gabor Lugosi

Bandits, Query Learning, and the Haystack Dimension

Kareem Amin, Michael Kearns, Umar Syed

Oracle inequalities for computationally budgeted model selection

Alekh Agarwal, John C. Duchi, Peter L. Bartlett, Clément Levrard

Competitive Closeness Testing

Jayadev Acharya, Hirakendu Das, Ashkan Jafarpour, Alon Orlitsky, Shengjun Pan

Blackwell Approachability and No-Regret Learning are Equivalent

Jacob Abernethy, Peter L. Bartlett, Elad Hazan

Regret Bounds for the Adaptive Control of Linear Quadratic Systems

Yasin Abbasi-Yadkori, Csaba Szepesvári