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2010
13 years 11 months ago
Simplifying Particle Swarm Optimization
The general purpose optimization method known as Particle Swarm Optimization (PSO) has received much attention in past years, with many attempts to find the variant that performs ...
M. E. H. Pedersen, Andrew J. Chipperfield
AR
2007
105views more  AR 2007»
13 years 11 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...
AR
2007
99views more  AR 2007»
13 years 11 months ago
Experience-based imitation using RNNPB
Abstract— Robot imitation is a useful and promising alternative to robot programming. Robot imitation involves two crucial issues. The first is how a robot can imitate a human w...
Ryunosuke Yokoya, Tetsuya Ogata, Jun Tani, Kazunor...
BC
2007
107views more  BC 2007»
13 years 11 months ago
Decoding spike train ensembles: tracking a moving stimulus
We consider the issue of how to read out the information from nonstationary spike train ensembles. Based on the theory of censored data in statistics, we propose a ‘censored’ m...
Enrico Rossoni, Jianfeng Feng
CORR
2010
Springer
103views Education» more  CORR 2010»
13 years 11 months ago
Spatially-Adaptive Reconstruction in Computed Tomography Based on Statistical Learning
We propose a direct reconstruction algorithm for Computed Tomography, based on a local fusion of a few preliminary image estimates by means of a non-linear fusion rule. One such ru...
Joseph Shtok, Michael Zibulevsky, Michael Elad