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» Optimizing Complex Loss Functions in Structured Prediction
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GD
2008
Springer
13 years 8 months ago
The Binary Stress Model for Graph Drawing
We introduce a new force-directed model for computing graph layout. The model bridges the two more popular force directed approaches – the stress and the electrical-spring models...
Yehuda Koren, Ali Civril
ICMCS
2009
IEEE
138views Multimedia» more  ICMCS 2009»
13 years 5 months ago
Multi-rate peer-to-peer video conferencing: A distributed approach using scalable coding
We consider multi-rate peer-to-peer multi-party conferencing applications, where different receivers in the same group can receive videos at different rates using, for example, sc...
Miroslav Ponec, Sudipta Sengupta, Minghua Chen, Ji...
EUROGP
1998
Springer
113views Optimization» more  EUROGP 1998»
13 years 12 months ago
Fitness Causes Bloat: Mutation
The problem of evolving, using mutation, an artificial ant to follow the Santa Fe trail is used to study the well known genetic programming feature of growth in solution length. Kn...
William B. Langdon, Riccardo Poli
GECCO
2006
Springer
218views Optimization» more  GECCO 2006»
13 years 11 months ago
Genetic programming with primitive recursion
When Genetic Programming is used to evolve arithmetic functions it often operates by composing them from a fixed collection of elementary operators and applying them to parameters...
Stefan Kahrs
PAMI
2010
396views more  PAMI 2010»
13 years 6 months ago
Self-Validated Labeling of Markov Random Fields for Image Segmentation
—This paper addresses the problem of self-validated labeling of Markov random fields (MRFs), namely to optimize an MRF with unknown number of labels. We present graduated graph c...
Wei Feng, Jiaya Jia, Zhi-Qiang Liu