Papers
176,624 papers found
Learning from Neighboring Strokes: Combining Appearance and Context for Multi-Domain Sketch Recognition
Tom Ouyang, Randall Davis
Learning GP-BayesFilters via Gaussian process latent variable models
J. Ko and D. Fox
Learning Halfspaces with Malicious Noise
Adam R. Klivans, Philip M. Long, Rocco A. Servedio
Learning in Markov Random Fields using Tempered Transitions
Ruslan Salakhutdinov
Learning Label Embeddings for Nearest-Neighbor Multi-class Classification with an Application to Speech Recognition
Natasha Singh-miller, Michael Collins
Learning Linear Ranking Functions for Beam Search with Application to Planning
Yuehua Xu, Alan Fern, Sungwook Yoon
Learning models of object structure
Joseph Schlecht, Kobus Barnard
Learning Nondeterministic Classifiers
Juan José del Coz, Jorge Díez, Antonio Bahamonde
Learning Non-Linear Combinations of Kernels
Corinna Cortes, Mehryar Mohri, Afshin Rostamizadeh
Learning of 2D grasping strategies from box-based 3D object approximations
S. Geidenstam, K. Huebner, D. Banksell and D. Kragic
Learning Permutations with Exponential Weights
David P. Helmbold, Manfred K. Warmuth
Learning to Explore and Exploit in POMDPs
Chenghui Cai, Xuejun Liao, Lawrence Carin
Learning to Hash with Binary Reconstructive Embeddings
Brian Kulis, Trevor Darrell
Learning to Rank by Optimizing NDCG Measure
Hamed Valizadegan, Rong Jin, Ruofei Zhang et al.
Learning transport operators for image manifolds
Benjamin Culpepper, Bruno A. Olshausen
Learning When Concepts Abound
Omid Madani, Michael Connor, Wiley Greiner
Learning with Compressible Priors
Volkan Cevher
Linear-time Algorithms for Pairwise Statistical Problems
Parikshit Ram, Dongryeol Lee, William March et al.
Locality-sensitive binary codes from shift-invariant kernels
Maxim Raginsky, Svetlana Lazebnik
Localizing Bugs in Program Executions with Graphical Models
Laura Dietz, Valentin Dallmeier, Andreas Zeller et al.
Local Rules for Global MAP: When Do They Work ?
Kyomin Jung, Pushmeet Kohli, Devavrat Shah
Lower bounds on minimax rates for nonparametric regression with additive sparsity and smoothness
Garvesh Raskutti, Bin Yu, Martin J. Wainwright
Low-Rank Kernel Learning with Bregman Matrix Divergences
Brian Kulis, Mátyás A. Sustik, Inderjit S. Dhillon