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» Evolutionary Approach to Test Generation for Functional BIST
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ICSE
2009
IEEE-ACM
14 years 3 months ago
Semantics-based code search
Our goal is to use the vast repositories of available open source code to generate specific functions or classes that meet a user’s specifications. The key words here are spec...
Steven P. Reiss
NIPS
2003
13 years 10 months ago
Semi-Supervised Learning with Trees
We describe a nonparametric Bayesian approach to generalizing from few labeled examples, guided by a larger set of unlabeled objects and the assumption of a latent tree-structure ...
Charles Kemp, Thomas L. Griffiths, Sean Stromsten,...
GECCO
2007
Springer
161views Optimization» more  GECCO 2007»
14 years 3 months ago
Alternative techniques to solve hard multi-objective optimization problems
In this paper, we propose the combination of different optimization techniques in order to solve “hard” two- and threeobjective optimization problems at a relatively low comp...
Ricardo Landa Becerra, Carlos A. Coello Coello, Al...
CEC
2007
IEEE
14 years 28 days ago
Virtual reality high dimensional objective spaces for multi-objective optimization: An improved representation
This paper presents an approach for constructing improved visual representations of high dimensional objective spaces using virtual reality. These spaces arise from the solution of...
Julio J. Valdés, Alan J. Barton, Robert Orc...
GECCO
2007
Springer
124views Optimization» more  GECCO 2007»
14 years 24 days ago
Fitness-proportional negative slope coefficient as a hardness measure for genetic algorithms
The Negative Slope Coefficient (nsc) is an empirical measure of problem hardness based on the analysis of offspring-fitness vs. parent-fitness scatterplots. The nsc has been teste...
Riccardo Poli, Leonardo Vanneschi