Papers
173,579 papers found
Learning Time-Intensity Profiles of Human Activity using Non-Parametric Bayesian Models
Alexander T. Ihler, Padhraic Smyth
Learning to be Bayesian without Supervision
Martin Raphan, Eero P. Simoncelli
Learning to Detect and Classify Malicious Executables in the Wild
J. Zico Kolter, Marcus A. Maloof
Learning to Model Spatial Dependency: Semi-Supervised Discriminative Random Fields
Chi-hoon Lee, Shaojun Wang, Feng Jiao et al.
Learning to parse images of articulated bodies
Deva Ramanan
Learning to Rank with Nonsmooth Cost Functions
Christopher J. Burges, Robert Ragno, Quoc V. Le
Learning to Traverse Image Manifolds
Piotr Dollár, Vincent Rabaud, Serge J. Belongie
Learning with Hypergraphs: Clustering, Classification, and Embedding
Dengyong Zhou, Jiayuan Huang, Bernhard Schölkopf
Linearly-solvable Markov decision problems
Emanuel Todorov
Linear Programming Relaxations and Belief Propagation -- An Empirical Study
Chen Yanover, Talya Meltzer, Yair Weiss
Linear Programs for Hypotheses Selection in Probabilistic Inference Models
Anders Bergkvist, Peter Damaschke, Marcel Lüthi
Linear State-Space Models for Blind Source Separation
Rasmus Kongsgaard Olsson, Lars Kai Hansen
LinguaStream: An Integrated Environment for Computational Linguistics Experimentation
Frédérik Bilhaut, Antoine Widlöcher
Logarithmic Online Regret Bounds for Undiscounted Reinforcement Learning
Peter Auer, Ronald Ortner
Logistic Regression for Single Trial EEG Classification
Ryota Tomioka, Kazuyuki Aihara, Klaus-Robert Müller
Lower Bounds and Aggregation in Density Estimation
Guillaume Lecué
Machine Learning for Computer Security
Philip K. Chan, Richard P. Lippmann
Manifold Denoising
Matthias Hein, Markus Maier
Map-Reduce for Machine Learning on Multicore
Cheng-tao Chu, Sang K. Kim, Yi-an Lin et al.
Maximum-Gain Working Set Selection for SVMs
Tobias Glasmachers, Christian Igel
Max-margin classification of incomplete data
Gal Chechik, Geremy Heitz, Gal Elidan et al.
MinReg: A Scalable Algorithm for Learning Parsimonious Regulatory Networks in Yeast and Mammals
Dana Pe'er, Amos Tanay, Aviv Regev
Mixture Regression for Covariate Shift
Masashi Sugiyama, Amos J. Storkey
MLLE: Modified Locally Linear Embedding Using Multiple Weights
Zhenyue Zhang, Jing Wang
Modeling Dyadic Data with Binary Latent Factors
Edward Meeds, Zoubin Ghahramani, Radford M. Neal et al.