Papers
Local Causal and Markov Blanket Induction for Causal Discovery and Feature Selection for Classification Part I: Algorithms and Empirical Evaluation
Constantin F. Aliferis, Alexander Statnikov, Ioannis Tsamardinos et al.
An Investigation of Missing Data Methods for Classification Trees Applied to Binary Response Data
Yufeng Ding, Jeffrey S. Simonoff
Classification Methods with Reject Option Based on Convex Risk Minimization
Ming Yuan, Marten Wegkamp
On-Line Sequential Bin Packing
András György, Gábor Lugosi, György Ottucsà
Model Selection: Beyond the Bayesian/Frequentist Divide
Isabelle Guyon, Amir Saffari, Gideon Dror et al.
Online Learning for Matrix Factorization and Sparse Coding
Julien Mairal, Francis Bach, Jean Ponce et al.
An Efficient Explanation of Individual Classifications using Game Theory
Erik Štrumbelj, Igor Kononenko
Exclusive Lasso for Multi-task Feature Selection
Yang Zhou, Rong Jin, Steven Chu–Hong Hoi
Matrix-Variate Dirichlet Process Mixture Models
Zhihua Zhang, Guang Dai, Michael I. Jordan
Bayesian Generalized Kernel Models
Zhihua Zhang, Guang Dai, Donghui Wang et al.
Multi-Task Learning using Generalized t Process
Yu Zhang, Dit–Yan Yeung
Bayesian Online Learning for Multi-label and Multi-variate Performance Measures
Xinhua Zhang, Thore Graepel, Ralf Herbrich
Risk Bounds for Levy Processes in the PAC-Learning Framework
Chao Zhang, Dacheng Tao
A highly efficient blocked Gibbs sampler reconstruction of multidimensional NMR spectra
Ji Won Yoon, Simon Wilson, K. Hun Mok
Modeling annotator expertise: Learning when everybody knows a bit of something
Yan Yan, Romer Rosales, Glenn Fung et al.
Dependent Indian Buffet Processes
Sinead Williamson, Peter Orbanz, Zoubin Ghahramani
Structured Prediction Cascades
David Weiss, Benjamin Taskar
Online Passive-Aggressive Algorithms on a Budget
Zhuang Wang, Slobodan Vucetic
A Potential-based Framework for Online Multi-class Learning with Partial Feedback
Shijun Wang, Rong Jin, Hamed Valizadegan
An Alternative Prior Process for Nonparametric Bayesian Clustering
Hanna Wallach, Shane Jensen, Lee Dicker et al.
Guarantees for Approximate Incremental SVMs
Nicolas Usunier, Antoine Bordes, Léon Bottou
Sequential Monte Carlo Samplers for Dirichlet Process Mixtures
Yener Ulker, Bilge Günsel, Taylan Cemgil
State-Space Inference and Learning with Gaussian Processes
Ryan Turner, Marc Deisenroth, Carl Rasmussen
Learning Causal Structure from Overlapping Variable Sets
Sofia Triantafillou, Ioannis Tsamardinos, Ioannis Tollis
A Markov-Chain Monte Carlo Approach to Simultaneous Localization and Mapping
Peter Torma, András György, Csaba Szepesvári