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ICMLA
2010
13 years 5 months ago
Nonlinear Dynamical Multi-Scale Model of Associative Memory
How can we get such reliable behavior from the mind when the brain is made up of such unreliable elements as neurons? We propose that the answer is related to the emergence of stab...
Alexander M. Duda, Stephen E. Levinson
JMLR
2012
11 years 9 months ago
Deep Boltzmann Machines as Feed-Forward Hierarchies
The deep Boltzmann machine is a powerful model that extracts the hierarchical structure of observed data. While inference is typically slow due to its undirected nature, we argue ...
Grégoire Montavon, Mikio L. Braun, Klaus-Ro...
ALIFE
2004
13 years 7 months ago
Adaptability and Diversity in Simulated Turn-taking Behavior
Turn-taking behavior is simulated in a coupled-agents system. Each agent is modeled as a mobile robot with two wheels. A recurrent neural network is used to produce the motor outpu...
Hiroyuki Iizuka, Takashi Ikegami
MEDINFO
2007
132views Healthcare» more  MEDINFO 2007»
13 years 8 months ago
Comparing Decision Support Methodologies for Identifying Asthma Exacerbations
Objective: To apply and compare common machine learning techniques with an expert-built Bayesian Network to determine eligibility for asthma guidelines in pediatric emergency depa...
Judith W. Dexheimer, Laura E. Brown, Jeffrey Leego...
GECCO
2007
Springer
149views Optimization» more  GECCO 2007»
14 years 1 months ago
Division blocks and the open-ended evolution of development, form, and behavior
We present a new framework for artificial life involving physically simulated, three-dimensional blocks called Division Blocks. Division Blocks can grow and shrink, divide and fo...
Lee Spector, Jon Klein, Mark Feinstein