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» Measuring the Complexity of Classification Problems
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TNN
2008
182views more  TNN 2008»
13 years 7 months ago
Large-Scale Maximum Margin Discriminant Analysis Using Core Vector Machines
Abstract--Large-margin methods, such as support vector machines (SVMs), have been very successful in classification problems. Recently, maximum margin discriminant analysis (MMDA) ...
Ivor Wai-Hung Tsang, András Kocsor, James T...
COMPLEXITY
2004
108views more  COMPLEXITY 2004»
13 years 7 months ago
On the convergence of a factorized distribution algorithm with truncation selection
nical Abstract Optimization is to find the "best" solution to a problem where the quality of a solution can be measured by a given criterion. Estimation of Distribution A...
Qingfu Zhang
NIPS
2004
13 years 9 months ago
Computing regularization paths for learning multiple kernels
The problem of learning a sparse conic combination of kernel functions or kernel matrices for classification or regression can be achieved via the regularization by a block 1-norm...
Francis R. Bach, Romain Thibaux, Michael I. Jordan
EUSFLAT
2007
147views Fuzzy Logic» more  EUSFLAT 2007»
13 years 9 months ago
Various Representations and Algebraic Structure of Linear Imprecision Indices
The paper is devoted to the investigation of imprecision indices, introduced in [7]. They are used for evaluation of uncertainty (or more exactly imprecision), which is contained ...
Alexander E. Lepskiy, Andrey G. Bronevich
CHI
2008
ACM
14 years 8 months ago
Feasibility and pragmatics of classifying working memory load with an electroencephalograph
A reliable and unobtrusive measurement of working memory load could be used to evaluate the efficacy of interfaces and to provide real-time user-state information to adaptive syst...
David B. Grimes, Desney S. Tan, Scott E. Hudson, P...