Papers
Universal Multi-Task Kernels
Andrea Caponnetto, Charles A. Micchelli, Massimiliano Pontil et al.
Dynamic Hierarchical Markov Random Fields for Integrated Web Data Extraction
Jun Zhu, Zaiqing Nie, Bo Zhang et al.
Aggregation of SVM Classifiers Using Sobolev Spaces
Sébastien Loustau
Learning to Combine Motor Primitives Via Greedy Additive Regression
Manu Chhabra, Robert A. Jacobs
Incremental Identification of Qualitative Models of Biological Systems using Inductive Logic Programming
Ashwin Srinivasan, Ross D. King
Causal Reasoning with Ancestral Graphs
Jiji Zhang
Online Learning of Complex Prediction Problems Using Simultaneous Projections
Yonatan Amit, Shai Shalev-Shwartz, Yoram Singer
Coordinate Descent Method for Large-scale L2-loss Linear Support Vector Machines
Kai-Wei Chang, Cho-Jui Hsieh, Chih-Jen Lin
A Bahadur Representation of the Linear Support Vector Machine
Ja-Yong Koo, Yoonkyung Lee, Yuwon Kim et al.
Using Markov Blankets for Causal Structure Learning
Jean-Philippe Pellet, André Elisseeff
Optimal Solutions for Sparse Principal Component Analysis
Alexandre d'Aspremont, Francis Bach, Laurent El Ghaoui
Maximal Causes for Non-linear Component Extraction
Jörg Lücke, Maneesh Sahani
Consistency of the Group Lasso and Multiple Kernel Learning
Francis R. Bach
A Multiple Instance Learning Strategy for Combating Good Word Attacks on Spam Filters
Zach Jorgensen, Yan Zhou, Meador Inge
Ranking Categorical Features Using Generalization Properties
Sivan Sabato, Shai Shalev-Shwartz
Consistency of Trace Norm Minimization
Francis R. Bach
Hit Miss Networks with Applications to Instance Selection
Elena Marchiori
Shark
Christian Igel, Verena Heidrich-Meisner, Tobias Glasmachers
Search for Additive Nonlinear Time Series Causal Models
Tianjiao Chu, Clark Glymour
Accelerated Neural Evolution through Cooperatively Coevolved Synapses
Faustino Gomez, Jürgen Schmidhuber, Risto Miikkulainen
Bouligand Derivatives and Robustness of Support Vector Machines for Regression
Andreas Christmann, Arnout Van Messem
Graphical Methods for Efficient Likelihood Inference in Gaussian Covariance Models
Mathias Drton, Thomas S. Richardson
An Error Bound Based on a Worst Likely Assignment
Eric Bax, Augusto Callejas