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» Learning similarity measures in non-orthogonal space
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COMPGEOM
2011
ACM
14 years 29 days ago
Comparing distributions and shapes using the kernel distance
Starting with a similarity function between objects, it is possible to define a distance metric (the kernel distance) on pairs of objects, and more generally on probability distr...
Sarang C. Joshi, Raj Varma Kommaraju, Jeff M. Phil...
KDD
2005
ACM
109views Data Mining» more  KDD 2005»
15 years 9 months ago
Formulating distance functions via the kernel trick
Tasks of data mining and information retrieval depend on a good distance function for measuring similarity between data instances. The most effective distance function must be for...
Gang Wu, Edward Y. Chang, Navneet Panda
ICRA
2002
IEEE
141views Robotics» more  ICRA 2002»
15 years 2 months ago
Movement Imitation with Nonlinear Dynamical Systems in Humanoid Robots
This article presents a new approach to movement planning, on-line trajectory modification, and imitation learning by representing movement plans based on a set of nonlinear di...
Auke Jan Ijspeert, Jun Nakanishi, Stefan Schaal
SIGIR
2005
ACM
15 years 3 months ago
Orthogonal locality preserving indexing
We consider the problem of document indexing and representation. Recently, Locality Preserving Indexing (LPI) was proposed for learning a compact document subspace. Different from...
Deng Cai, Xiaofei He
MM
2004
ACM
152views Multimedia» more  MM 2004»
15 years 2 months ago
Manifold-ranking based image retrieval
In this paper, we propose a novel transductive learning framework named manifold-ranking based image retrieval (MRBIR). Given a query image, MRBIR first makes use of a manifold ra...
Jingrui He, Mingjing Li, HongJiang Zhang, Hanghang...