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ICML
2007
IEEE
15 years 11 months ago
An empirical evaluation of deep architectures on problems with many factors of variation
Recently, several learning algorithms relying on models with deep architectures have been proposed. Though they have demonstrated impressive performance, to date, they have only b...
Hugo Larochelle, Dumitru Erhan, Aaron C. Courville...
AAAI
2011
13 years 10 months ago
Sparse Matrix-Variate t Process Blockmodels
We consider the problem of modeling network interactions and identifying latent groups of network nodes. This problem is challenging due to the facts i) that the network nodes are...
Zenglin Xu, Feng Yan, Yuan Qi
JITECH
2010
106views more  JITECH 2010»
14 years 9 months ago
Patterns and structures of intra-organizational learning networks within a knowledge-intensive organization
This paper employs the network perspective to study patterns and structures of intraorganizational learning networks. The theoretical background draws from cognitive theories, the...
Miha Skerlavaj, Vlado Dimovski, Kevin C. Desouza
CORR
2010
Springer
104views Education» more  CORR 2010»
14 years 10 months ago
Empirical learning aided by weak domain knowledge in the form of feature importance
Standard hybrid learners that use domain knowledge require stronger knowledge that is hard and expensive to acquire. However, weaker domain knowledge can benefit from prior knowle...
Ridwan Al Iqbal
ASUNAM
2010
IEEE
15 years 5 days ago
Semi-Supervised Classification of Network Data Using Very Few Labels
The goal of semi-supervised learning (SSL) methods is to reduce the amount of labeled training data required by learning from both labeled and unlabeled instances. Macskassy and Pr...
Frank Lin, William W. Cohen