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» Modeling Classification and Inference Learning
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SDM
2010
SIAM
200views Data Mining» more  SDM 2010»
13 years 9 months ago
Residual Bayesian Co-clustering for Matrix Approximation
In recent years, matrix approximation for missing value prediction has emerged as an important problem in a variety of domains such as recommendation systems, e-commerce and onlin...
Hanhuai Shan, Arindam Banerjee
NIPS
2000
13 years 9 months ago
Rate-coded Restricted Boltzmann Machines for Face Recognition
We describe a neurally-inspired, unsupervised learning algorithm that builds a non-linear generative model for pairs of face images from the same individual. Individuals are then ...
Yee Whye Teh, Geoffrey E. Hinton
JMLR
2010
115views more  JMLR 2010»
13 years 2 months ago
Fast and Scalable Local Kernel Machines
A computationally efficient approach to local learning with kernel methods is presented. The Fast Local Kernel Support Vector Machine (FaLK-SVM) trains a set of local SVMs on redu...
Nicola Segata, Enrico Blanzieri
CHI
2009
ACM
14 years 8 months ago
A biologically inspired approach to learning multimodal commands and feedback for human-robot interaction
In this paper we describe a method to enable a robot to learn how a user gives commands and feedback to it by speech, prosody and touch. We propose a biologically inspired approac...
Anja Austermann, Seiji Yamada
COGSCI
2004
142views more  COGSCI 2004»
13 years 8 months ago
Characterizing perceptual learning with external noise
Performance in perceptual tasks often improves with practice. This effect is known as `perceptual learning,' and it has been the source of a great deal of interest and debate...
Jason M. Gold, Allison B. Sekuler, Partrick J. Ben...