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ESANN
2007
15 years 7 months ago
Replacing eligibility trace for action-value learning with function approximation
The eligibility trace is one of the most used mechanisms to speed up reinforcement learning. Earlier reported experiments seem to indicate that replacing eligibility traces would p...
Kary Främling
NIPS
2007
15 years 7 months ago
Using Deep Belief Nets to Learn Covariance Kernels for Gaussian Processes
We show how to use unlabeled data and a deep belief net (DBN) to learn a good covariance kernel for a Gaussian process. We first learn a deep generative model of the unlabeled da...
Ruslan Salakhutdinov, Geoffrey E. Hinton
ICML
2004
IEEE
16 years 6 months ago
Lookahead-based algorithms for anytime induction of decision trees
The majority of the existing algorithms for learning decision trees are greedy--a tree is induced top-down, making locally optimal decisions at each node. In most cases, however, ...
Saher Esmeir, Shaul Markovitch
DATE
2003
IEEE
82views Hardware» more  DATE 2003»
15 years 11 months ago
A Circuit SAT Solver With Signal Correlation Guided Learning
— Boolean Satistifiability has attracted tremendous research effort in recent years, resulting in the developments of various efficient SAT solver packages. Based upon their de...
Feng Lu, Li-C. Wang, Kwang-Ting Cheng, Ric C.-Y. H...
UAI
2001
15 years 7 months ago
Improved learning of Bayesian networks
The search space of Bayesian Network structures is usually defined as Acyclic Directed Graphs (DAGs) and the search is done by local transformations of DAGs. But the space of Baye...
Tomás Kocka, Robert Castelo