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EUROGP
2007
Springer
135views Optimization» more  EUROGP 2007»
14 years 2 months ago
A Grammatical Genetic Programming Approach to Modularity in Genetic Algorithms
The ability of Genetic Programming to scale to problems of increasing difficulty operates on the premise that it is possible to capture regularities that exist in a problem environ...
Erik Hemberg, Conor Gilligan, Michael O'Neill, Ant...
CVPR
1998
IEEE
14 years 10 months ago
Action Recognition Using Probabilistic Parsing
A new approach to the recognition of temporal behaviors and activities is presented. The fundamental idea, inspired by work in speech recognition, is to divide the inference probl...
Aaron F. Bobick, Yuri A. Ivanov
INFOCOM
2003
IEEE
14 years 1 months ago
On Guaranteed Smooth Scheduling For Input-Queued Switches
— Input-queued switches are used extensively in the design of high-speed routers. As switch speeds and sizes increase, the design of the switch scheduler becomes a primary challe...
Isaac Keslassy, Murali S. Kodialam, T. V. Lakshman...
ICCV
2009
IEEE
15 years 1 months ago
Efficient Discriminative Learning of Parts-based Models
Supervised learning of a parts-based model can be for- mulated as an optimization problem with a large (exponen- tial in the number of parts) set of constraints. We show how thi...
M. Pawan Kumar, Andrew Zisserman, Philip H.S. Torr
RECOMB
2003
Springer
14 years 8 months ago
Maximum entropy modeling of short sequence motifs with applications to RNA splicing signals
We propose a framework for modeling sequence motifs based on the maximum entropy principle (MEP). We recommend approximating short sequence motif distributions with the maximum en...
Gene W. Yeo, Christopher B. Burge