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JMLR
2012
13 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...
GECCO
2009
Springer
148views Optimization» more  GECCO 2009»
16 years 1 months ago
An evolutionary approach to constructive induction for link discovery
This paper presents a genetic programming-based symbolic regression approach to the construction of relational features in link analysis applications. Specifically, we consider t...
Tim Weninger, William H. Hsu, Jing Xia, Waleed Alj...
CEC
2005
IEEE
16 years 9 days ago
Coevolution of neural Go players in a cultural environment
Abstract- We present experiments (co)evolving Go players based on artificial neural networks (ANNs) for a 5x5 board. ANN structure and weights are encoded in multi–chromosomal g...
Helmut A. Mayer, Peter Maier
DATE
2005
IEEE
143views Hardware» more  DATE 2005»
16 years 9 days ago
galsC: A Language for Event-Driven Embedded Systems
— We introduce galsC, a language designed for programming event-driven embedded systems such as sensor networks. galsC implements the TinyGALS programming model. At the local lev...
Elaine Cheong, Jie Liu
ICANN
1997
Springer
15 years 10 months ago
On Learning Soccer Strategies
We use simulated soccer to study multiagent learning. Each team's players (agents) share action set and policy but may behave differently due to position-dependent inputs. All...
Rafal Salustowicz, Marco Wiering, Jürgen Schm...