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ESANN
2006
15 years 5 months ago
On the selection of hidden neurons with heuristic search strategies for approximation
Abstract. Feature Selection techniques usually follow some search strategy to select a suitable subset from a set of features. Most neural network growing algorithms perform a sear...
Ignacio Barrio, Enrique Romero, Lluís A. Be...
UAI
2003
15 years 5 months ago
Approximate Decomposition: A Method for Bounding and Estimating Probabilistic and Deterministic Queries
In this paper, we introduce a method for approximating the solution to inference and optimization tasks in uncertain and deterministic reasoning. Such tasks are in general intract...
David Larkin
147
Voted
ISMB
1998
15 years 5 months ago
Compression of Strings with Approximate Repeats
We describe a model for strings of characters that is loosely based on the Lempel Ziv model with the addition that a repeated substring can be an approximate match to the original...
Lloyd Allison, Timothy Edgoose, Trevor I. Dix
EMNLP
2010
15 years 1 months ago
Turbo Parsers: Dependency Parsing by Approximate Variational Inference
We present a unified view of two state-of-theart non-projective dependency parsers, both approximate: the loopy belief propagation parser of Smith and Eisner (2008) and the relaxe...
André F. T. Martins, Noah A. Smith, Eric P....
ICML
1996
IEEE
15 years 8 months ago
A Convergent Reinforcement Learning Algorithm in the Continuous Case: The Finite-Element Reinforcement Learning
This paper presents a direct reinforcement learning algorithm, called Finite-Element Reinforcement Learning, in the continuous case, i.e. continuous state-space and time. The eval...
Rémi Munos