Papers
176,624 papers found
Dynamic Task Assignment in Robot Swarms
James McLurkin, Daniel Yamins
Effcient Motion Planning Based on Disassembly
Yuandong Yang, Oliver Brock
Efficient Computation of Gapped Substring Kernels on Large Alphabets
Juho Rousu, John Shawe-Taylor
Efficient Exploration With Latent Structure
Bethany R. Leffler, Michael L. Littman, Alexander L. Strehl et al.
Efficient Margin Maximizing with Boosting
Gunnar Rätsch, Manfred K. Warmuth
Estimating Functions for Blind Separation When Sources Have Variance Dependencies
Motoaki Kawanabe, Klaus-Robert Mü
Expectation Consistent Approximate Inference
Manfred Opper, Ole Winther
Fast Kernel Classifiers with Online and Active Learning
Antoine Bordes, Seyda Ertekin, Jason Weston et al.
Frames, Reproducing Kernels, Regularization and Learning
Alain Rakotomamonjy, Stéphane Canu
Gaussian Processes for Ordinal Regression
Wei Chu, Zoubin Ghahramani
Generalization Bounds for the Area Under the ROC Curve
Shivani Agarwal, Thore Graepel, Ralf Herbrich et al.
Information Bottleneck for Gaussian Variables
Gal Chechik, Amir Globerson, Naftali Tishby et al.
Inner Product Spaces for Bayesian Networks
Atsuyoshi Nakamura, Michael Schmitt, Niels Schmitt et al.
Interacting Markov Random Fields for Simultaneous Terrain Modeling and Obstacle Detection
Carl Wellington, Aaron Courville, Anthony Stentz
Kernel Methods for Measuring Independence
Arthur Gretton, Ralf Herbrich, Alexander Smola et al.
Large Margin Methods for Structured and Interdependent Output Variables
Ioannis Tsochantaridis, Thorsten Joachims, Thomas Hofmann et al.
Learning a Mahalanobis Metric from Equivalence Constraints
Aharon Bar-Hillel, Tomer Hertz, Noam Shental et al.
Learning from Examples as an Inverse Problem
Ernesto De Vito, Lorenzo Rosasco, Andrea Caponnetto et al.
Learning Hidden Variable Networks: The Information Bottleneck Approach
Gal Elidan, Nir Friedman
Learning Module Networks
Eran Segal, Dana Pe'er, Aviv Regev et al.
Learning Multiple Tasks with Kernel Methods
Theodoros Evgeniou, Charles A. Micchelli, Massimiliano Pontil
Learning the Kernel Function via Regularization
Charles A. Micchelli, Massimiliano Pontil