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» Probabilistic Neural Network Models for Sequential Data
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UAI
1997
13 years 9 months ago
Exploring Parallelism in Learning Belief Networks
It has been shown that a class of probabilistic domain models cannot be learned correctly by several existing algorithms which employ a single-link lookahead search. When a multil...
Tongsheng Chu, Yang Xiang
ROMAN
2007
IEEE
179views Robotics» more  ROMAN 2007»
14 years 2 months ago
A Bayesian Network Framework for Vision Based Semantic Scene Understanding
— For a robot to understand a scene, we have to infer and extract meaningful information from vision sensor data. Since scene understanding consists in recognizing several visual...
Seung-Bin Im, Keum-Sung Hwang, Sung-Bae Clio
INFOCOM
2006
IEEE
14 years 2 months ago
Establishing Pair-Wise Keys in Heterogeneous Sensor Networks
— Many applications that make use of sensor networks require secure communication. Because asymmetric-key solutions are difficult to implement in such a resource-constrained env...
Patrick Traynor, Heesook Choi, Guohong Cao, Sencun...
DAGSTUHL
2009
13 years 9 months ago
Statistical Mechanics of On-line Learning
We introduce and discuss the application of statistical physics concepts in the context of on-line machine learning processes. The consideration of typical properties of very large...
Michael Biehl, Nestor Caticha, Peter Riegler
INFORMATICALT
2007
95views more  INFORMATICALT 2007»
13 years 7 months ago
Neuro-IG: A Hybrid System for Selection and Elimination of Predictor Variables and non Relevant Individuals
In this article we present the general architecture of a hybrid neuro-symbolic system for the selection and stepwise elimination of predictor variables and non-relevant individuals...
Baghdad Atmani, Bouziane Beldjilali