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AR
2007
105views more  AR 2007»
15 years 6 months ago
Reinforcement learning of a continuous motor sequence with hidden states
—Reinforcement learning is the scheme for unsupervised learning in which robots are expected to acquire behavior skills through self-explorations based on reward signals. There a...
Hiroaki Arie, Tetsuya Ogata, Jun Tani, Shigeki Sug...
ALMOB
2006
80views more  ALMOB 2006»
15 years 6 months ago
Effective p-value computations using Finite Markov Chain Imbedding (FMCI): application to local score and to pattern statistics
The technique of Finite Markov Chain Imbedding (FMCI) is a classical approach to complex combinatorial problems related to sequences. In order to get efficient algorithms, it is k...
Grégory Nuel
IJAHUC
2006
128views more  IJAHUC 2006»
15 years 6 months ago
Avoid 'void' in geographic routing for data aggregation in sensor networks
: Wireless sensor networks have attracted great attention in research and industrial development due to its fast-growing application potentials. New techniques must be developed fo...
Shigang Chen, Guangbin Fan, Jun-Hong Cui
CORR
2007
Springer
128views Education» more  CORR 2007»
15 years 6 months ago
Model Selection Through Sparse Maximum Likelihood Estimation
We consider the problem of estimating the parameters of a Gaussian or binary distribution in such a way that the resulting undirected graphical model is sparse. Our approach is to...
Onureena Banerjee, Laurent El Ghaoui, Alexandre d'...
GPEM
2002
163views more  GPEM 2002»
15 years 6 months ago
Fast Ant Colony Optimization on Runtime Reconfigurable Processor Arrays
Ant Colony Optimization (ACO) is a metaheuristic used to solve combinatorial optimization problems. As with other metaheuristics, like evolutionary methods, ACO algorithms often sh...
Daniel Merkle, Martin Middendorf