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NIPS
2007
15 years 6 months ago
Sparse Feature Learning for Deep Belief Networks
Unsupervised learning algorithms aim to discover the structure hidden in the data, and to learn representations that are more suitable as input to a supervised machine than the ra...
Marc'Aurelio Ranzato, Y-Lan Boureau, Yann LeCun
UAI
1996
15 years 6 months ago
Learning Equivalence Classes of Bayesian Network Structures
Two Bayesian-network structures are said to be equivalent if the set of distributions that can be represented with one of those structures is identical to the set of distributions...
David Maxwell Chickering
ENC
2004
IEEE
15 years 8 months ago
A Method Based on Genetic Algorithms and Fuzzy Logic to Induce Bayesian Networks
A method to induce bayesian networks from data to overcome some limitations of other learning algorithms is proposed. One of the main features of this method is a metric to evalua...
Manuel Martínez-Morales, Ramiro Garza-Dom&i...
148
Voted
CE
2008
122views more  CE 2008»
15 years 5 months ago
Ubiquitous learning website: Scaffold learners by mobile devices with information-aware techniques
The portability and immediate communication properties of mobile devices influence the learning processes in interacting with peers, accessing resources and transferring data. For...
G. D. Chen, C. K. Chang, C. Y. Wang
155
Voted
UAI
2000
15 years 6 months ago
Tractable Bayesian Learning of Tree Belief Networks
In this paper we present decomposable priors, a family of priors over structure and parameters of tree belief nets for which Bayesian learning with complete observations is tracta...
Marina Meila, Tommi Jaakkola