Papers
184,605 papers found
Kernel Maximum Entropy Data Transformation and an Enhanced Spectral Clustering Algorithm
Robert Jenssen, Torbjørn Eltoft, Mark Girolami et al.
Kernels on Prolog Proof Trees: Statistical Learning in the ILP Setting
Andrea Passerini, Paolo Frasconi, Luc De Raedt
Kernels on Structured Objects Through Nested Histograms
Marco Cuturi, Kenji Fukumizu
Large Margin Component Analysis
Lorenzo Torresani, Kuang-chih Lee
Large Margin Hidden Markov Models for Automatic Speech Recognition
Fei Sha, Lawrence K. Saul
Large Margin Multi-channel Analog-to-Digital Conversion with Applications to Neural Prosthesis
Amit Gore, Shantanu Chakrabartty
Large Scale Hidden Semi-Markov SVMs
Gunnar Rätsch, Sören Sonnenburg
Large Scale Multiple Kernel Learning
Sören Sonnenburg, Gunnar Rätsch, Christin Schäfer et al.
Large-Scale Sparsified Manifold Regularization
Ivor W. Tsang, James T. Kwok
Large Scale Transductive SVMs
Ronan Collobert, Fabian Sinz, Jason Weston et al.
Learning a Hidden Hypergraph
Dana Angluin, Jiang Chen
Learning annotated hierarchies from relational data
Daniel M. Roy, Charles Kemp, Vikash K. Mansinghka et al.
Learning Coordinate Covariances via Gradients
Sayan Mukherjee, Ding-Xuan Zhou
Learning Dense 3D Correspondence
Florian Steinke, Volker Blanz, Bernhard Schölkopf
Learning Factor Graphs in Polynomial Time and Sample Complexity
Pieter Abbeel, Daphne Koller, Andrew Y. Ng
Learning from Multiple Sources
Koby Crammer, Michael Kearns, Jennifer Wortman
Learning Image Components for Object Recognition
Michael W. Spratling
Learning Minimum Volume Sets
Clayton D. Scott, Robert D. Nowak
Learning Motion Style Synthesis from Perceptual Observations
Lorenzo Torresani, Peggy Hackney, Christoph Bregler
Learning Nonparametric Models for Probabilistic Imitation
David B. Grimes, Daniel R. Rashid, Rajesh P. Rao
Learning on Graph with Laplacian Regularization
Rie K. Ando, Tong Zhang
Learning Operational Space Control
J. Peters, S. Schaal
Learning Parts-Based Representations of Data
David A. Ross, Richard S. Zemel
Learning Recursive Control Programs from Problem Solving
Pat Langley, Dongkyu Choi
Learning Sparse Representations by Non-Negative Matrix Factorization and Sequential Cone Programming
Matthias Heiler, Christoph Schnörr