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» Computational model for amygdala neural networks
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NEUROSCIENCE
2001
Springer
15 years 6 months ago
Biological Grounding of Recruitment Learning and Vicinal Algorithms in Long-Term Potentiation
Biological networks are capable of gradual learning based on observing a large number of exemplars over time as well as of rapidly memorizing specific events as a result of a sin...
Lokendra Shastri
103
Voted
IPPS
1998
IEEE
15 years 6 months ago
Multiprocessor Scheduling Using Mean-Field Annealing
This paper presents our work on the static task scheduling model using the mean-field annealing (MFA) technique. Mean-field annealing is a technique of thermostatic annealing that...
Shaharuddin Salleh, Albert Y. Zomaya
JMLR
2012
13 years 4 months ago
Random Search for Hyper-Parameter Optimization
Grid search and manual search are the most widely used strategies for hyper-parameter optimization. This paper shows empirically and theoretically that randomly chosen trials are ...
James Bergstra, Yoshua Bengio
NC
2010
159views Neural Networks» more  NC 2010»
15 years 11 days ago
Automata and processes on multisets of communicating objects
Abstract. Inspired by P systems initiated by Gheorghe P˜aun, we study a computation model over a multiset of communicating objects. The objects in our model are instances of fini...
Linmin Yang, Yong Wang, Zhe Dang
IJCNN
2006
IEEE
15 years 8 months ago
Studies on Sparse Array Cortical Modeling and Memory Cognition Duality
— In this paper we have suggested a sparse three dimensional array model for the brain. Entries of the array are synaptic weights as functions of time. This is a typical four dim...
Kausik Kumar Majumdar, Robert Kozma