Papers
Nonparametric Quantile Estimation
Ichiro Takeuchi, Quoc V. Le, Timothy D. Sears et al.
Worst-Case Analysis of Selective Sampling for Linear Classification
Nicoló Cesa-Bianchi, Claudio Gentile, Luca Zaniboni
A Very Fast Learning Method for Neural Networks Based on Sensitivity Analysis
Enrique Castillo, Bertha Guijarro-Berdiñas, Oscar Fontenla-Romero et al.
New Algorithms for Efficient High-Dimensional Nonparametric Classification
Ting Liu, Andrew W. Moore, Alexander Gray
Step Size Adaptation in Reproducing Kernel Hilbert Space
S. V. N. Vishwanathan, Nicol N. Schraudolph, Alex J. Smola
Action Elimination and Stopping Conditions for the Multi-Armed Bandit and Reinforcement Learning Problems
Eyal Even-Dar, Shie Mannor, Yishay Mansour
A Graphical Representation of Equivalence Classes of AMP Chain Graphs
Alberto Roverato, Milan Studený
One-Class Novelty Detection for Seizure Analysis from Intracranial EEG
Andrew B. Gardner, Abba M. Krieger, George Vachtsevanos et al.
Sparse Boosting
Peter Bühlmann, Bin Yu
Quantile Regression Forests
Nicolai Meinshausen
Lower Bounds and Aggregation in Density Estimation
Guillaume Lecué
Segmental Hidden Markov Models with Random Effects for Waveform Modeling
Seyoung Kim, Padhraic Smyth
Rearrangement Clustering: Pitfalls, Remedies, and Applications
Sharlee Climer, Weixiong Zhang
Evolutionary Function Approximation for Reinforcement Learning
Shimon Whiteson, Peter Stone
Infinite-Ï Limits For Tikhonov Regularization
Ross A. Lippert, Ryan M. Rifkin
Consistency and Convergence Rates of One-Class SVMs and Related Algorithms
Régis Vert, Jean-Philippe Vert
Learning Image Components for Object Recognition
Michael W. Spratling
Policy Gradient in Continuous Time
Rémi Munos
QP Algorithms with Guaranteed Accuracy and Run Time for Support Vector Machines
Don Hush, Patrick Kelly, Clint Scovel et al.
Some Theory for Generalized Boosting Algorithms
Peter J. Bickel, Ya'acov Ritov, Alon Zakai
Learning Minimum Volume Sets
Clayton D. Scott, Robert D. Nowak
Pattern Recognition for Conditionally Independent Data
Daniil Ryabko
Stochastic Complexities of Gaussian Mixtures in Variational Bayesian Approximation
Kazuho Watanabe, Sumio Watanabe
A Direct Method for Building Sparse Kernel Learning Algorithms
Mingrui Wu, Bernhard Schölkopf, Gökhan Bakir