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» Margin Distribution and Learning
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181
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PPSN
2004
Springer
16 years 11 days ago
Learning Probabilistic Tree Grammars for Genetic Programming
Genetic Programming (GP) provides evolutionary methods for problems with tree representations. A recent development in Genetic Algorithms (GAs) has led to principled algorithms cal...
Peter A. N. Bosman, Edwin D. de Jong
110
Voted
ICS
2010
Tsinghua U.
15 years 11 months ago
High-throughput Bayesian network learning using heterogeneous multicore computers
Michael D. Linderman, Robert Bruggner, Vivek Athal...
207
Voted
ICMLA
2010
15 years 5 months ago
Multimodal Parameter-exploring Policy Gradients
Abstract-- Policy Gradients with Parameter-based Exploration (PGPE) is a novel model-free reinforcement learning method that alleviates the problem of high-variance gradient estima...
Frank Sehnke, Alex Graves, Christian Osendorfer, J...
200
Voted
ICML
2009
IEEE
16 years 7 months ago
Learning structurally consistent undirected probabilistic graphical models
In many real-world domains, undirected graphical models such as Markov random fields provide a more natural representation of the dependency structure than directed graphical mode...
Sushmita Roy, Terran Lane, Margaret Werner-Washbur...
COLT
2003
Springer
16 years 7 days ago
A General Class of No-Regret Learning Algorithms and Game-Theoretic Equilibria
A general class of no-regret learning algorithms, called no-Φ-regret learning algorithms, is defined which spans the spectrum from no-external-regret learning to no-internal-reg...
Amy R. Greenwald, Amir Jafari