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MP
2010
154views more  MP 2010»
13 years 7 months ago
A null-space primal-dual interior-point algorithm for nonlinear optimization with nice convergence properties
Abstract. We present a null-space primal-dual interior-point algorithm for solving nonlinear optimization problems with general inequality and equality constraints. The algorithm a...
Xinwei Liu, Yaxiang Yuan
ISSAC
2009
Springer
167views Mathematics» more  ISSAC 2009»
14 years 3 months ago
High order derivatives and decomposition of multivariate polynomials
In this paper, we present an improved method for decomposing multivariate polynomials. This problem, also known as the Functional Decomposition Problem (FDP) [17, 9, 27], is class...
Jean-Charles Faugère, Ludovic Perret
IDA
2005
Springer
14 years 2 months ago
Condensed Nearest Neighbor Data Domain Description
—A simple yet effective unsupervised classification rule to discriminate between normal and abnormal data is based on accepting test objects whose nearest neighbors’ distances ...
Fabrizio Angiulli
NIPS
1997
13 years 10 months ago
Mapping a Manifold of Perceptual Observations
Nonlinear dimensionality reduction is formulated here as the problem of trying to find a Euclidean feature-space embedding of a set of observations that preserves as closely as p...
Joshua B. Tenenbaum
ICASSP
2010
IEEE
13 years 9 months ago
Evaluation of random-projection-based feature combination on speech recognition
Random projection has been suggested as a means of dimensionality reduction, where the original data are projected onto a subspace using a random matrix. It represents a computati...
Tetsuya Takiguchi, Jeff Bilmes, Mariko Yoshii, Yas...