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» Convex Programming Methods for Global Optimization
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ICML
2007
IEEE
14 years 8 months ago
Multiclass multiple kernel learning
In many applications it is desirable to learn from several kernels. "Multiple kernel learning" (MKL) allows the practitioner to optimize over linear combinations of kern...
Alexander Zien, Cheng Soon Ong
ECAI
2008
Springer
13 years 9 months ago
Optimizing Causal Link Based Web Service Composition
Automation of Web service composition is one of the most interesting challenges facing the Semantic Web today. Since Web services have been enhanced with formal semantic descriptio...
Freddy Lécué, Alexandre Delteil, Ala...
ICML
2010
IEEE
13 years 8 months ago
Learning Efficiently with Approximate Inference via Dual Losses
Many structured prediction tasks involve complex models where inference is computationally intractable, but where it can be well approximated using a linear programming relaxation...
Ofer Meshi, David Sontag, Tommi Jaakkola, Amir Glo...
ICCV
2009
IEEE
15 years 16 days 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
GECCO
2005
Springer
136views Optimization» more  GECCO 2005»
14 years 1 months ago
Exploring extended particle swarms: a genetic programming approach
Particle Swarm Optimisation (PSO) uses a population of particles that fly over the fitness landscape in search of an optimal solution. The particles are controlled by forces tha...
Riccardo Poli, Cecilia Di Chio, William B. Langdon