Papers
4,122 papers found
Discriminative Learning Under Covariate Shift
Steffen Bickel, Michael Brückner, Tobias Scheffer
Distance Metric Learning for Large Margin Nearest Neighbor Classification
Kilian Q. Weinberger, Lawrence K. Saul
Distributed Algorithms for Topic Models
David Newman, Arthur Asuncion, Padhraic Smyth et al.
Dlib-ml: A Machine Learning Toolkit
Davis E. King
DL-Learner: Learning Concepts in Description Logics
Jens Lehmann
Efficient Online and Batch Learning Using Forward Backward Splitting
John Duchi, Yoram Singer
Entropy Inference and the James-Stein Estimator, with Application to Nonlinear Gene Association Networks
Jean Hausser, Korbinian Strimmer
Estimating Labels from Label Proportions
Novi Quadrianto, Alex J. Smola, Tibério S. Caetano et al.
Estimation of Sparse Binary Pairwise Markov Networks using Pseudo-likelihoods
Holger Höfling, Robert Tibshirani
Evolutionary Model Type Selection for Global Surrogate Modeling
Dirk Gorissen, Tom Dhaene, Filip De Turck
Exploiting Product Distributions to Identify Relevant Variables of Correlation Immune Functions
Lisa Hellerstein, Bernard Rosell, Eric Bach et al.
Exploring Strategies for Training Deep Neural Networks
Hugo Larochelle, Yoshua Bengio, Jérôme Louradour et al.
Fast Approximate kNN Graph Construction for High Dimensional Data via Recursive Lanczos Bisection
Jie Chen, Haw-ren Fang, Yousef Saad
Feature Selection with Ensembles, Artificial Variables, and Redundancy Elimination
Eugene Tuv, Alexander Borisov, George Runger et al.
Fourier Theoretic Probabilistic Inference over Permutations
Jonathan Huang, Carlos Guestrin, Leonidas Guibas
Generalization Bounds for Ranking Algorithms via Algorithmic Stability
Shivani Agarwal, Partha Niyogi
Hash Kernels for Structured Data
Qinfeng Shi, James Petterson, Gideon Dror et al.
Hybrid MPI/OpenMP Parallel Linear Support Vector Machine Training
Kristian Woodsend, Jacek Gondzio
Identification of Recurrent Neural Networks by Bayesian Interrogation Techniques
Barnabás Póczos, András Loőrincz
Improving the Reliability of Causal Discovery from Small Data Sets Using Argumentation
Facundo Bromberg, Dimitris Margaritis
Incorporating Functional Knowledge in Neural Networks
Charles Dugas, Yoshua Bengio, François Bélisle et al.
Java-ML: A Machine Learning Library
Thomas Abeel, Yves Van de Peer, Yvan Saeys
Learning Acyclic Probabilistic Circuits Using Test Paths
Dana Angluin, James Aspnes, Jiang Chen et al.
Learning Approximate Sequential Patterns for Classification
Zeeshan Syed, Piotr Indyk, John Guttag
Learning Halfspaces with Malicious Noise
Adam R. Klivans, Philip M. Long, Rocco A. Servedio