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» Learning for stochastic dynamic programming
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148
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HCW
1999
IEEE
15 years 7 months ago
Multiple Cost Optimization for Task Assignment in Heterogeneous Computing Systems Using Learning Automata
A framework for task assignment in heterogeneous computing systems is presented in this work. The framework is based on a learning automata model. The proposed model can be used f...
Raju D. Venkataramana, N. Ranganathan
138
Voted
UAI
2004
15 years 4 months ago
Bayesian Learning in Undirected Graphical Models: Approximate MCMC Algorithms
Bayesian learning in undirected graphical models--computing posterior distributions over parameters and predictive quantities-is exceptionally difficult. We conjecture that for ge...
Iain Murray, Zoubin Ghahramani
129
Voted
IJON
2010
119views more  IJON 2010»
15 years 1 months ago
Hyperparameter learning in probabilistic prototype-based models
We present two approaches to extend Robust Soft Learning Vector Quantization (RSLVQ). This algorithm for nearest prototype classification is derived from an explicit cost functio...
Petra Schneider, Michael Biehl, Barbara Hammer
114
Voted
BC
2002
84views more  BC 2002»
15 years 2 months ago
Hebbian spike-driven synaptic plasticity for learning patterns of mean firing rates
Synaptic plasticity is believed to underlie the formation of appropriate patterns of connectivity that stabilize stimulus-selective reverberations in the cortex. Here we present a ...
Stefano Fusi
110
Voted
CEC
2010
IEEE
15 years 3 months ago
Learning to overtake in TORCS using simple reinforcement learning
In modern racing games programming non-player characters with believable and sophisticated behaviors is getting increasingly challenging. Recently, several works in the literature ...
Daniele Loiacono, Alessandro Prete, Pier Luca Lanz...