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220
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CDC
2008
IEEE
15 years 6 months ago
2008
IEEE
Minimizing the rank of a matrix subject to constraints is a challenging problem that arises in many applications in control theory, machine learning, and discrete geometry. This c...
133
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AAMAS
2006
Springer
15 years 6 months ago
2006
Springer
Abstract. There are many domains in which a multi-agent system needs to maximize a "system utility" function which rates the performance of the entire system, while subje...
160
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CORR
2010
Springer
15 years 4 months ago
2010
Springer
Structured output prediction is an important machine learning problem both in theory and practice, and the max-margin Markov network (M3 N) is an effective approach. All state-of-...
200
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CVPR
2004
IEEE
16 years 8 months ago
2004
IEEE
Model-based clustering of motion trajectories can be posed as the problem of learning an underlying mixture density function whose components correspond to motion classes with dif...
171
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GECCO
2010
Springer
15 years 11 months ago
2010
Springer
Negative selection algorithms are immune-inspired classifiers that are trained on negative examples only. Classification is performed by generating detectors that match none of ...