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ICML
2003
IEEE
15 years 10 months ago
Learning Metrics via Discriminant Kernels and Multidimensional Scaling: Toward Expected Euclidean Representation
Distance-based methods in machine learning and pattern recognition have to rely on a metric distance between points in the input space. Instead of specifying a metric a priori, we...
Zhihua Zhang
INTERACT
2007
14 years 11 months ago
Towards Metrics for Web Accessibility Evaluation
Nowadays, accessibility is a crucial factor for Web site development and use, and yet, people with visual disabilities face many accessibility barriers that hinder the adequate un...
Sinésio Teles de Lima, Fernanda Lima, K&aac...
NIPS
2004
14 years 11 months ago
Triangle Fixing Algorithms for the Metric Nearness Problem
Various problems in machine learning, databases, and statistics involve pairwise distances among a set of objects. It is often desirable for these distances to satisfy the propert...
Inderjit S. Dhillon, Suvrit Sra, Joel A. Tropp
SIAMJO
2008
79views more  SIAMJO 2008»
14 years 9 months ago
A Class of Inexact Variable Metric Proximal Point Algorithms
For the problem of solving maximal monotone inclusions, we present a rather general class of algorithms, which contains hybrid inexact proximal point methods as a special case and ...
Lisandro A. Parente, Pablo A. Lotito, Mikhail V. S...
CVPR
2008
IEEE
14 years 11 months ago
Classification via semi-Riemannian spaces
In this paper, we develop a geometric framework for linear or nonlinear discriminant subspace learning and classification. In our framework, the structures of classes are conceptu...
Deli Zhao, Zhouchen Lin, Xiaoou Tang