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JCP
2007
143views more  JCP 2007»
13 years 7 months ago
Noisy K Best-Paths for Approximate Dynamic Programming with Application to Portfolio Optimization
Abstract— We describe a general method to transform a non-Markovian sequential decision problem into a supervised learning problem using a K-bestpaths algorithm. We consider an a...
Nicolas Chapados, Yoshua Bengio
ICTAI
2010
IEEE
13 years 5 months ago
Continuous Search in Constraint Programming
This work presents the concept of Continuous Search (CS), which objective is to allow any user to eventually get their constraint solver achieving a top performance on their proble...
Alejandro Arbelaez, Youssef Hamadi, Michèle...
GECCO
2007
Springer
181views Optimization» more  GECCO 2007»
14 years 1 months ago
A study on metamodeling techniques, ensembles, and multi-surrogates in evolutionary computation
Surrogate-Assisted Memetic Algorithm(SAMA) is a hybrid evolutionary algorithm, particularly a memetic algorithm that employs surrogate models in the optimization search. Since mos...
Dudy Lim, Yew-Soon Ong, Yaochu Jin, Bernhard Sendh...
IJCNN
2000
IEEE
14 years 1 days ago
Storage and Recall of Complex Temporal Sequences through a Contextually Guided Self-Organizing Neural Network
A self-organizing neural network for learning and recall of complex temporal sequences is proposed. we consider a single sequence with repeated items, or several sequences with a c...
Guilherme De A. Barreto, Aluizio F. R. Araú...
COLT
2000
Springer
13 years 12 months ago
PAC Analogues of Perceptron and Winnow via Boosting the Margin
We describe a novel family of PAC model algorithms for learning linear threshold functions. The new algorithms work by boosting a simple weak learner and exhibit complexity bounds...
Rocco A. Servedio