Papers
MULTIBOOST: A Multi-purpose Boosting Package
Djalel Benbouzid, Róbert Busa-Fekete, Norman Casagrande et al.
Metric and Kernel Learning Using a Linear Transformation
Prateek Jain, Brian Kulis, Jason V. Davis et al.
Eliminating Spammers and Ranking Annotators for Crowdsourced Labeling Tasks
Vikas C. Raykar, Shipeng Yu
Multi-Assignment Clustering for Boolean Data
Mario Frank, Andreas P. Streich, David Basin et al.
Online Learning in the Embedded Manifold of Low-rank Matrices
Uri Shalit, Daphna Weinshall, Gal Chechik
Minimax-Optimal Rates For Sparse Additive Models Over Kernel Classes Via Convex Programming
Garvesh Raskutti, Martin J. Wainwright, Bin Yu
Bounding the Probability of Error for High Precision Optical Character Recognition
Gary B. Huang, Andrew Kae, Carl Doersch et al.
Noise-Contrastive Estimation of Unnormalized Statistical Models, with Applications to Natural Image Statistics
Michael U. Gutmann, Aapo Hyvärinen
Random Search for Hyper-Parameter Optimization
James Bergstra, Yoshua Bengio
Active Learning via Perfect Selective Classification
Ran El-Yaniv, Yair Wiener
Multi Kernel Learning with Online-Batch Optimization
Francesco Orabona, Luo Jie, Barbara Caputo
Active Clustering of Biological Sequences
Konstantin Voevodski, Maria-Florina Balcan, Heiko Röglin et al.
Optimal Distributed Online Prediction Using Mini-Batches
Ofer Dekel, Ran Gilad-Bachrach, Ohad Shamir et al.
Refinement of Operator-valued Reproducing Kernels
Haizhang Zhang, Yuesheng Xu, Qinghui Zhang
Plug-in Approach to Active Learning
Stanislav Minsker
Conditional Likelihood Maximisation: A Unifying Framework for Information Theoretic Feature Selection
Gavin Brown, Adam Pocock, Ming-Jie Zhao et al.
Distance Metric Learning with Eigenvalue Optimization
Yiming Ying, Peng Li
Open Problem: Does AdaBoost Always Cycle?
Cynthia Rudin, Robert E. Schapire, Ingrid Daubechies
Open Problem: Learning Dynamic Network Models from a Static Snapshot
Jan Ramon, Constantin Comendant
Open Problem: Better Bounds for Online Logistic Regression
H. Brendan McMahan, Matthew Streeter
The Best of Both Worlds: Stochastic and Adversarial Bandits
Sébastien Bubeck, Aleksandrs Slivkins
Towards Minimax Policies for Online Linear Optimization with Bandit Feedback
Sébastien Bubeck, Nicoló Cesa-Bianchi, Sham M. Kakade
Autonomous Exploration For Navigating In MDPs
Shiau Hong Lim, Peter Auer