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AAAI
2004
13 years 7 months ago
Distributed Representation of Syntactic Structure by Tensor Product Representation and Non-Linear Compression
Representing lexicons and sentences with the subsymbolic approach (using techniques such as Self Organizing Map (SOM) or Artificial Neural Network (ANN)) is a relatively new but i...
Heidi H. T. Yeung, Peter W. M. Tsang
CA
2003
IEEE
13 years 11 months ago
Expressive Gesture Animation Based on Non Parametric Learning of Sensory-Motor Models
This paper presents an efficient method of learning motion control for autonomous animated characters. The method uses a non parametric learning approach which identifies non line...
Sylvie Gibet, Pierre-Francois Marteau
JMLR
2010
125views more  JMLR 2010»
13 years 1 months ago
Stochastic Complexity and Generalization Error of a Restricted Boltzmann Machine in Bayesian Estimation
In this paper, we consider the asymptotic form of the generalization error for the restricted Boltzmann machine in Bayesian estimation. It has been shown that obtaining the maximu...
Miki Aoyagi
ML
2002
ACM
133views Machine Learning» more  ML 2002»
13 years 5 months ago
Estimating Generalization Error on Two-Class Datasets Using Out-of-Bag Estimates
For two-class datasets, we provide a method for estimating the generalization error of a bag using out-of-bag estimates. In bagging, each predictor (single hypothesis) is learned ...
Tom Bylander
CSE
2009
IEEE
14 years 1 months ago
Self-Tuning the Parameter of Adaptive Non-linear Sampling Method for Flow Statistics
—Flow statistics is a basic task of passive measurement and has been widely used to characterize the state of the network. Adaptive Non-Linear Sampling (ANLS)is one of the most a...
Chengchen Hu, Bin Liu