Papers
Optimization Techniques for Semi-Supervised Support Vector Machines
Olivier Chapelle, Vikas Sindhwani, Sathiya S. Keerthi
Evidence Contrary to the Statistical View of Boosting
David Mease, Abraham Wyner
Active Learning by Spherical Subdivision
Falk-Florian Henrich, Klaus Obermayer
Discriminative Learning of Max-Sum Classifiers
Vojtěch Franc, Bogdan Savchynskyy
On the Suitable Domain for SVM Training in Image Coding
Gustavo Camps-Valls, Juan Gutiérrez, Gabriel Gómez-Pérez et al.
Linear-Time Computation of Similarity Measures for Sequential Data
Konrad Rieck, Pavel Laskov
Max-margin Classification of Data with Absent Features
Gal Chechik, Geremy Heitz, Gal Elidan et al.
Scalable Algorithms for String Kernels with Inexact Matching
Pavel P. Kuksa, Pai-hsi Huang, Vladimir Pavlovic
The Mondrian Process
Daniel M. Roy, Yee W. Teh
One sketch for all: Theory and Application of Conditional Random Sampling
Ping Li, Kenneth W. Church, Trevor J. Hastie
Temporal Difference Based Actor Critic Learning - Convergence and Neural Implementation
Dotan D. Castro, Dmitry Volkinshtein, Ron Meir
Clustered Multi-Task Learning: A Convex Formulation
Laurent Jacob, Jean-philippe Vert, Francis R. Bach
Human Active Learning
Rui M. Castro, Charles Kalish, Robert Nowak et al.
Predictive Indexing for Fast Search
Sharad Goel, John Langford, Alexander L. Strehl
Modeling Short-term Noise Dependence of Spike Counts in Macaque Prefrontal Cortex
Arno Onken, Steffen Grünewälder, Matthias Munk et al.
Multiscale Random Fields with Application to Contour Grouping
Longin J. Latecki, Chengen Lu, Marc Sobel et al.
On the Generalization Ability of Online Strongly Convex Programming Algorithms
Sham M. Kakade, Ambuj Tewari
Fitted Q-iteration by Advantage Weighted Regression
Gerhard Neumann, Jan R. Peters
Simple Local Models for Complex Dynamical Systems
Erik Talvitie, Satinder P. Singh
Nonlinear causal discovery with additive noise models
Patrik O. Hoyer, Dominik Janzing, Joris M. Mooij et al.
Non-stationary dynamic Bayesian networks
Joshua W. Robinson, Alexander J. Hartemink
On the Design of Loss Functions for Classification: theory, robustness to outliers, and SavageBoost
Hamed Masnadi-shirazi, Nuno Vasconcelos
Variational Mixture of Gaussian Process Experts
Chao Yuan, Claus Neubauer
Online Optimization in X-Armed Bandits
Sébastien Bubeck, Gilles Stoltz, Csaba Szepesvári et al.
Learning the Semantic Correlation: An Alternative Way to Gain from Unlabeled Text
Yi Zhang, Artur Dubrawski, Jeff G. Schneider