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» Modeling Classification and Inference Learning
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SDM
2010
SIAM
200views Data Mining» more  SDM 2010»
15 years 6 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
15 years 6 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»
14 years 11 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
16 years 5 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»
15 years 4 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...