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ICML
2008
IEEE
16 years 4 days ago
Nearest hyperdisk methods for high-dimensional classification
In high-dimensional classification problems it is infeasible to include enough training samples to cover the class regions densely. Irregularities in the resulting sparse sample d...
Hakan Cevikalp, Bill Triggs, Robi Polikar
ICANN
2005
Springer
15 years 4 months ago
The LCCP for Optimizing Kernel Parameters for SVM
Abstract. Tuning hyper-parameters is a necessary step to improve learning algorithm performances. For Support Vector Machine classifiers, adjusting kernel parameters increases dra...
Sabri Boughorbel, Jean-Philippe Tarel, Nozha Bouje...
ATVA
2008
Springer
102views Hardware» more  ATVA 2008»
15 years 1 months ago
Time-Progress Evaluation for Dense-Time Automata with Concave Path Conditions
The evaluation of successor or predecessor state spaces through time progress is a central component in the model-checking algorithm of dense-time automata. The definition of the t...
Farn Wang
CDC
2009
IEEE
151views Control Systems» more  CDC 2009»
15 years 4 months ago
A poset framework to model decentralized control problems
— In this paper we use partially ordered sets (posets) to study decentralized control problems arising in different settings. We show that time delayed systems with certain dela...
Parikshit Shah, Pablo A. Parrilo
ICML
2009
IEEE
16 years 4 days ago
Learning kernels from indefinite similarities
Similarity measures in many real applications generate indefinite similarity matrices. In this paper, we consider the problem of classification based on such indefinite similariti...
Yihua Chen, Maya R. Gupta, Benjamin Recht