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» Methods for convex and general quadratic programming
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ICML
2009
IEEE
16 years 5 months 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
AUTOMATICA
2007
72views more  AUTOMATICA 2007»
15 years 4 months ago
A probabilistic analytic center cutting plane method for feasibility of uncertain LMIs
ust control problems can be formulated in abstract form as convex feasibility programs, where one seeks a solution x that satisfies a set of inequalities of the form F . = {f (x,...
Giuseppe C. Calafiore, Fabrizio Dabbene
HAPTICS
2002
IEEE
15 years 9 months ago
Optimal Design Method for Selective Nerve Stimulation and Its Application to Electrocutaneous Display
We have developed a tactile display that uses electric current from the skin surface as a stimulus. Our main objective was to independently stimulate a variety of mechanoreceptors...
Hiroyuki Kajimoto, Naoki Kawakami, Susumu Tachi
JMLR
2008
168views more  JMLR 2008»
15 years 4 months ago
Max-margin Classification of Data with Absent Features
We consider the problem of learning classifiers in structured domains, where some objects have a subset of features that are inherently absent due to complex relationships between...
Gal Chechik, Geremy Heitz, Gal Elidan, Pieter Abbe...
CORR
2008
Springer
142views Education» more  CORR 2008»
15 years 4 months ago
A Gaussian Belief Propagation Solver for Large Scale Support Vector Machines
Support vector machines (SVMs) are an extremely successful type of classification and regression algorithms. Building an SVM entails solving a constrained convex quadratic program...
Danny Bickson, Elad Yom-Tov, Danny Dolev