Papers
4,122 papers found
MedLDA: Maximum Margin Supervised Topic Models
Jun Zhu, Amr Ahmed, Eric P. Xing
Metric and Kernel Learning Using a Linear Transformation
Prateek Jain, Brian Kulis, Jason V. Davis et al.
Minimax Manifold Estimation
Christopher Genovese, Marco Perone-Pacifico, Isabella Verdinelli et al.
Minimax-Optimal Rates For Sparse Additive Models Over Kernel Classes Via Convex Programming
Garvesh Raskutti, Martin J. Wainwright, Bin Yu
Mixability is Bayes Risk Curvature Relative to Log Loss
Tim van Erven, Mark D. Reid, Robert C. Williamson
ML-Flex: A Flexible Toolbox for Performing Classification Analyses In Parallel
Stephen R. Piccolo, Lewis J. Frey
Multi-Assignment Clustering for Boolean Data
Mario Frank, Andreas P. Streich, David Basin et al.
MULTIBOOST: A Multi-purpose Boosting Package
Djalel Benbouzid, Róbert Busa-Fekete, Norman Casagrande et al.
Multi-Instance Learning with Any Hypothesis Class
Sivan Sabato, Naftali Tishby
Multi Kernel Learning with Online-Batch Optimization
Francesco Orabona, Luo Jie, Barbara Caputo
Multi-Target Regression with Rule Ensembles
Timo Aho, Bernard Ženko, Sašo Džeroski et al.
Multi-task Regression using Minimal Penalties
Matthieu Solnon, Sylvain Arlot, Francis Bach
NIMFA : A Python Library for Nonnegative Matrix Factorization
Marinka Žitnik, Blaž Zupan
Noise-Contrastive Estimation of Unnormalized Statistical Models, with Applications to Natural Image Statistics
Michael U. Gutmann, Aapo Hyvärinen
Nonparametric Guidance of Autoencoder Representations using Label Information
Jasper Snoek, Ryan P. Adams, Hugo Larochelle
Non-Sparse Multiple Kernel Fisher Discriminant Analysis
Fei Yan, Josef Kittler, Krystian Mikolajczyk et al.
Oger: Modular Learning Architectures For Large-Scale Sequential Processing
David Verstraeten, Benjamin Schrauwen, Sander Dieleman et al.
Online Learning in the Embedded Manifold of Low-rank Matrices
Uri Shalit, Daphna Weinshall, Gal Chechik
Online Submodular Minimization
Elad Hazan, Satyen Kale
On Ranking and Generalization Bounds
Wojciech Rejchel
On the Convergence Rate of -Norm Multiple Kernel Learning
Marius Kloft, Gilles Blanchard
On the Necessity of Irrelevant Variables
David P. Helmbold, Philip M. Long
Optimal Distributed Online Prediction Using Mini-Batches
Ofer Dekel, Ran Gilad-Bachrach, Ohad Shamir et al.
Optimistic Bayesian Sampling in Contextual-Bandit Problems
Benedict C. May, Nathan Korda, Anthony Lee et al.
PAC-Bayes Bounds with Data Dependent Priors
Emilio Parrado-Hernández, Amiran Ambroladze, John Shawe-Taylor et al.