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GECCO
2009
Springer
258views Optimization» more  GECCO 2009»
15 years 4 months ago
Evolutionary learning of local descriptor operators for object recognition
Nowadays, object recognition is widely studied under the paradigm of matching local features. This work describes a genetic programming methodology that synthesizes mathematical e...
Cynthia B. Pérez, Gustavo Olague
GECCO
2007
Springer
183views Optimization» more  GECCO 2007»
15 years 3 months ago
Evolving distributed agents for managing air traffic
Air traffic management offers an intriguing real world challenge to designing large scale distributed systems using evolutionary computation. The ability to evolve effective air t...
Adrian K. Agogino, Kagan Tumer
CP
2008
Springer
15 years 1 months ago
An Application of Constraint Programming to Superblock Instruction Scheduling
Modern computer architectures have complex features that can only be fully taken advantage of if the compiler schedules the compiled code. A standard region of code for scheduling ...
Abid M. Malik, Michael Chase, Tyrel Russell, Peter...
KDD
2007
ACM
132views Data Mining» more  KDD 2007»
16 years 4 days ago
A scalable modular convex solver for regularized risk minimization
A wide variety of machine learning problems can be described as minimizing a regularized risk functional, with different algorithms using different notions of risk and different r...
Choon Hui Teo, Alex J. Smola, S. V. N. Vishwanatha...
AAAI
2000
15 years 1 months ago
Decision Making under Uncertainty: Operations Research Meets AI (Again)
Models for sequential decision making under uncertainty (e.g., Markov decision processes,or MDPs) have beenstudied in operations research for decades. The recent incorporation of ...
Craig Boutilier