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JCP
2007
121views more  JCP 2007»
15 years 6 months ago
Learning by Discrimination: A Constructive Incremental Approach
Abstract— This paper presents i-AA1 , a constructive, incremental learning algorithm for a special class of weightless, self-organizing networks. In i-AA1 , learning consists of ...
Christophe G. Giraud-Carrier, Tony R. Martinez
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JCP
2007
143views more  JCP 2007»
15 years 6 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
JCSS
2007
116views more  JCSS 2007»
15 years 6 months ago
The most probable annotation problem in HMMs and its application to bioinformatics
Hidden Markov models (HMMs) are often used for biological sequence annotation. Each sequence feature is represented by a collection of states with the same label. In annotating a ...
Brona Brejová, Daniel G. Brown 0001, Tom&aa...
TOG
2008
130views more  TOG 2008»
15 years 6 months ago
Quadrilateral mesh simplification
We introduce a simplification algorithm for meshes composed of quadrilateral elements. It is reminiscent of edge-collapse based methods for triangle meshes, but takes a novel appr...
Joel Daniels II, Cláudio T. Silva, Jason Sh...
TWC
2008
117views more  TWC 2008»
15 years 6 months ago
Channel predictive proportional fair scheduling
There is growing interest in the area of cross-layer design. This paper addresses the problem of multi-user diversity scheduling together with channel prediction. Recent work demo...
Hans Jørgen Bang, Torbjörn Ekman, Davi...
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