Papers
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
Finite-Time Bounds for Fitted Value Iteration
Rémi Munos, Csaba Szepesvári
Bayesian Inference and Optimal Design for the Sparse Linear Model
Matthias W. Seeger
Multi-class Discriminant Kernel Learning via Convex Programming
Jieping Ye, Shuiwang Ji, Jianhui Chen
Learning Control Knowledge for Forward Search Planning
Sungwook Yoon, Alan Fern, Robert Givan
Graphical Models for Structured Classification, with an Application to Interpreting Images of Protein Subcellular Location Patterns
Shann-Ching Chen, Geoffrey J. Gordon, Robert F. Murphy
Trust Region Newton Method for Logistic Regression
Chih-Jen Lin, Ruby C. Weng, S. Sathiya Keerthi
A Library for Locally Weighted Projection Regression
Stefan Klanke, Sethu Vijayakumar, Stefan Schaal
Learning Reliable Classifiers From Small or Incomplete Data Sets: The Naive Credal Classifier 2
Giorgio Corani, Marco Zaffalon
Closed Sets for Labeled Data
Gemma C. Garriga, Petra Kralj, Nada Lavrač
An Information Criterion for Variable Selection in Support Vector Machines
Gerda Claeskens, Christophe Croux, Johan Van Kerckhoven
Estimating the Confidence Interval for Prediction Errors of Support Vector Machine Classifiers
Bo Jiang, Xuegong Zhang, Tianxi Cai
Model Selection Through Sparse Maximum Likelihood Estimation for Multivariate Gaussian or Binary Data
Onureena Banerjee, Laurent El Ghaoui, Alexandre d'Aspremont
A Recursive Method for Structural Learning of Directed Acyclic Graphs
Xianchao Xie, Zhi Geng
Theoretical Advantages of Lenient Learners: An Evolutionary Game Theoretic Perspective
Liviu Panait, Karl Tuyls, Sean Luke
A Tutorial on Conformal Prediction
Glenn Shafer, Vladimir Vovk
Generalization from Observed to Unobserved Features by Clustering
Eyal Krupka, Naftali Tishby
Algorithms for Sparse Linear Classifiers in the Massive Data Setting
Suhrid Balakrishnan, David Madigan
Support Vector Machinery for Infinite Ensemble Learning
Hsuan-Tien Lin, Ling Li
Near-Optimal Sensor Placements in Gaussian Processes: Theory, Efficient Algorithms and Empirical Studies
Andreas Krause, Ajit Singh, Carlos Guestrin