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MSE
2005
IEEE
133views Hardware» more  MSE 2005»
15 years 6 months ago
Embedded System Design with FPGAs Using HDLs (Lessons Learned and Pitfalls to Be Avoided)
This paper describes the authors experience with teaching VHDL (and more recently, Verilog) to undergraduate and graduate students at WPI and to engineers through various short co...
R. James Duckworth
EUROGP
2010
Springer
166views Optimization» more  EUROGP 2010»
15 years 5 months ago
Learning a Lot from Only a Little: Genetic Programming for Panel Segmentation on Sparse Sensory Evaluation Data
We describe a data mining framework that derives panelist information from sparse flavour survey data. One component of the framework executes genetic programming ensemble based s...
Katya Vladislavleva, Kalyan Veeramachaneni, Una-Ma...
94
Voted
GECCO
2006
Springer
167views Optimization» more  GECCO 2006»
15 years 4 months ago
Genomic computing networks learn complex POMDPs
A genomic computing network is a variant of a neural network for which a genome encodes all aspects, both structural and functional, of the network. The genome is evolved by a gen...
David J. Montana, Eric Van Wyk, Marshall Brinn, Jo...
110
Voted
ICML
2008
IEEE
16 years 1 months ago
Predicting diverse subsets using structural SVMs
In many retrieval tasks, one important goal involves retrieving a diverse set of results (e.g., documents covering a wide range of topics for a search query). First of all, this r...
Yisong Yue, Thorsten Joachims
NN
2006
Springer
120views Neural Networks» more  NN 2006»
15 years 14 days ago
Computational intelligence in earth sciences and environmental applications: Issues and challenges
This paper introduces a generic theoretical framework for predictive learning, and relates it to data-driven and learning applications in earth and environmental sciences. The iss...
Vladimir Cherkassky, Vladimir M. Krasnopolsky, Dim...