Papers
Estimating Functions for Blind Separation When Sources Have Variance Dependencies
Motoaki Kawanabe, Klaus-Robert Mü
Learning with Decision Lists of Data-Dependent Features
Mario Marchand, Marina Sokolova
Generalization Bounds for the Area Under the ROC Curve
Shivani Agarwal, Thore Graepel, Ralf Herbrich et al.
Core Vector Machines: Fast SVM Training on Very Large Data Sets
Ivor W. Tsang, James T. Kwok, Pak-Ming Cheung
A Modified Finite Newton Method for Fast Solution of Large Scale Linear SVMs
S. Sathiya Keerthi, Dennis DeCoste
Denoising Source Separation
Jaakko Särelä, Harri Valpola
A Classification Framework for Anomaly Detection
Ingo Steinwart, Don Hush, Clint Scovel
Multiclass Boosting for Weak Classifiers
Günther Eibl, Karl-Peter Pfeiffer
Information Bottleneck for Gaussian Variables
Gal Chechik, Amir Globerson, Naftali Tishby et al.
Diffusion Kernels on Statistical Manifolds
John Lafferty, Guy Lebanon
Learning Hidden Variable Networks: The Information Bottleneck Approach
Gal Elidan, Nir Friedman
Stability of Randomized Learning Algorithms
Andre Elisseeff, Theodoros Evgeniou, Massimiliano Pontil
Dimension Reduction in Text Classification with Support Vector Machines
Hyunsoo Kim, Peg Howland, Haesun Park
Asymptotic Model Selection for Naive Bayesian Networks
Dmitry Rusakov, Dan Geiger
The Dynamics of AdaBoost: Cyclic Behavior and Convergence of Margins
Cynthia Rudin, Ingrid Daubechies, Robert E. Schapire
Fast Binary Feature Selection with Conditional Mutual Information
François Fleuret
Variance Reduction Techniques for Gradient Estimates in Reinforcement Learning
Evan Greensmith, Peter L. Bartlett, Jonathan Baxter
Non-negative Matrix Factorization with Sparseness Constraints
Patrik O. Hoyer
Fast String Kernels using Inexact Matching for Protein Sequences
Christina Leslie, Rui Kuang
Second Order Cone Programming Formulations for Feature Selection
Chiranjib Bhattacharyya
The Entire Regularization Path for the Support Vector Machine
Trevor Hastie, Saharon Rosset, Robert Tibshirani et al.
Some Properties of Regularized Kernel Methods
Ernesto De Vito, Lorenzo Rosasco, Andrea Caponnetto et al.