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NIPS
1994
15 years 7 months ago
A Non-linear Information Maximisation Algorithm that Performs Blind Separation
A new learning algorithmis derived which performs online stochastic gradient ascent in the mutual informationbetween outputs and inputs of a network. In the absence of a priori kn...
Anthony J. Bell, Terrence J. Sejnowski
IJON
2006
112views more  IJON 2006»
15 years 6 months ago
Comparison of automated parameter estimation methods for neuronal signaling networks
This work is a suitability study of the different optimization methods for automated parameter estimation (fitting) in the context of neuronal signaling networks. The Gepasi simul...
Antti Pettinen, Olli Yli-Harja, Marja-Leena Linne
AIPS
2008
15 years 8 months ago
Multiagent Planning Under Uncertainty with Stochastic Communication Delays
We consider the problem of cooperative multiagent planning under uncertainty, formalized as a decentralized partially observable Markov decision process (Dec-POMDP). Unfortunately...
Matthijs T. J. Spaan, Frans A. Oliehoek, Nikos A. ...
IOR
2010
112views more  IOR 2010»
15 years 4 months ago
New Policies for the Stochastic Inventory Control Problem with Two Supply Sources
We study an inventory system under periodic review in the presence of two suppliers (or delivery modes). The emergency supplier has a shorter lead-time than the regular supplier, ...
Anshul Sheopuri, Ganesh Janakiraman, Sridhar Sesha...
ICML
2000
IEEE
16 years 7 months ago
Convergence Problems of General-Sum Multiagent Reinforcement Learning
Stochastic games are a generalization of MDPs to multiple agents, and can be used as a framework for investigating multiagent learning. Hu and Wellman (1998) recently proposed a m...
Michael H. Bowling