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JMLR
2010
198views more  JMLR 2010»
13 years 6 months ago
On Learning with Integral Operators
A large number of learning algorithms, for example, spectral clustering, kernel Principal Components Analysis and many manifold methods are based on estimating eigenvalues and eig...
Lorenzo Rosasco, Mikhail Belkin, Ernesto De Vito
ECCV
2006
Springer
14 years 9 months ago
Riemannian Manifold Learning for Nonlinear Dimensionality Reduction
In recent years, nonlinear dimensionality reduction (NLDR) techniques have attracted much attention in visual perception and many other areas of science. We propose an efficient al...
Tony Lin, Hongbin Zha, Sang Uk Lee
ICMCS
2005
IEEE
79views Multimedia» more  ICMCS 2005»
14 years 1 months ago
Supervised semi-definite embedding for image manifolds
Semi-definite Embedding (SDE) has been a recently proposed to maximize the sum of pair wise squared distances between outputs while the input data and outputs are locally isometri...
Benyu Zhang, Jun Yan, Ning Liu, QianSheng Cheng, Z...
TVCG
2008
70views more  TVCG 2008»
13 years 7 months ago
Visualizing Incomplete and Partially Ranked Data
Ranking data, which result from m raters ranking n items, are difficult to visualize due to their discrete algebraic structure, and the computational difficulties associated with t...
Paul Kidwell, Guy Lebanon, William S. Cleveland
VLDB
2004
ACM
129views Database» more  VLDB 2004»
14 years 26 days ago
Probabilistic Ranking of Database Query Results
We investigate the problem of ranking answers to a database query when many tuples are returned. We adapt and apply principles of probabilistic models from Information Retrieval f...
Surajit Chaudhuri, Gautam Das, Vagelis Hristidis, ...