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» Machine Learning by Function Decomposition
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ICML
2003
IEEE
15 years 6 months ago
The Significance of Temporal-Difference Learning in Self-Play Training TD-Rummy versus EVO-rummy
Reinforcement learning has been used for training game playing agents. The value function for a complex game must be approximated with a continuous function because the number of ...
Clifford Kotnik, Jugal K. Kalita
IJON
2007
184views more  IJON 2007»
15 years 1 months ago
Convex incremental extreme learning machine
Unlike the conventional neural network theories and implementations, Huang et al. [Universal approximation using incremental constructive feedforward networks with random hidden n...
Guang-Bin Huang, Lei Chen
ICA
2012
Springer
13 years 9 months ago
On Revealing Replicating Structures in Multiway Data: A Novel Tensor Decomposition Approach
A novel tensor decomposition called pattern or P-decomposition is proposed to make it possible to identify replicating structures in complex data, such as textures and patterns in ...
Anh Huy Phan, Andrzej Cichocki, Petr Tichavsk&yacu...
COLT
2007
Springer
15 years 7 months ago
How Good Is a Kernel When Used as a Similarity Measure?
Recently, Balcan and Blum [1] suggested a theory of learning based on general similarity functions, instead of positive semi-definite kernels. We study the gap between the learnin...
Nathan Srebro
BMCBI
2006
75views more  BMCBI 2006»
15 years 1 months ago
A machine learning strategy to identify candidate binding sites in human protein-coding sequence
Background: The splicing of RNA transcripts is thought to be partly promoted and regulated by sequences embedded within exons. Known sequences include binding sites for SR protein...
Thomas Down, Bernard Leong, Tim J. P. Hubbard