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ICML
2005
IEEE
16 years 7 months ago
Active learning for Hidden Markov Models: objective functions and algorithms
Hidden Markov Models (HMMs) model sequential data in many fields such as text/speech processing and biosignal analysis. Active learning algorithms learn faster and/or better by cl...
Brigham Anderson, Andrew Moore
GECCO
2006
Springer
185views Optimization» more  GECCO 2006»
15 years 10 months ago
Robot gaits evolved by combining genetic algorithms and binary hill climbing
In this paper an evolutionary algorithm is used for evolving gaits in a walking biped robot controller. The focus is fast learning in a real-time environment. An incremental appro...
Lena Mariann Garder, Mats Erling Høvin
COMPGEOM
2008
ACM
15 years 8 months ago
Self-improving algorithms for delaunay triangulations
We study the problem of two-dimensional Delaunay triangulation in the self-improving algorithms model [1]. We assume that the n points of the input each come from an independent, ...
Kenneth L. Clarkson, C. Seshadhri
IMECS
2007
15 years 8 months ago
A Genetic Algorithm for Optimizing Facility Layout in a Wafer Fab
—In this research, the Genetic Algorithm (GA) and Space-Filling Curve (SFC) are combined along with the use of Taguchi method for finding the optimal combination of parameters. T...
Michael H. Hu, Meei-Yuh Ku, Chao-Chi Chen
CORR
2008
Springer
133views Education» more  CORR 2008»
15 years 6 months ago
Approximation Algorithms for Shortest Descending Paths in Terrains
A path from s to t on a polyhedral terrain is descending if the height of a point p never increases while we move p along the path from s to t. No efficient algorithm is known to ...
Mustaq Ahmed, Sandip Das, Sachin Lodha, Anna Lubiw...