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» Clustering Large Datasets in Arbitrary Metric Spaces
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SAC
2004
ACM
14 years 24 days ago
Time-frequency feature detection for time-course microarray data
Gene clustering based on microarray data provides useful functional information to the working biologists. Many current gene-clustering algorithms rely on Euclidean-based distance...
Jiawu Feng, Paolo Emilio Barbano, Bud Mishra
IWCMC
2006
ACM
14 years 1 months ago
Performance of Taroko: a cluster-based addressing and routing scheme for self-organized networks
Self-Organized Networks (SONs) are a general description of autonomous networks without infrastructure, of which Ad Hoc, Sensor and Mesh networks are special cases. We had previou...
Julien Ridoux, Meriem Kassar, Mathias Boc, Anne Fl...
ECCV
2010
Springer
14 years 18 days ago
Fast Approximate Nearest Neighbor Methods for Non-Euclidean Manifolds with Applications to Human Activity Analysis in Videos
Approximate Nearest Neighbor (ANN) methods such as Locality Sensitive Hashing, Semantic Hashing, and Spectral Hashing, provide computationally ecient procedures for nding objects...
Rizwan Chaudhry, Yuri Ivanov
ECCV
2002
Springer
14 years 9 months ago
Nonlinear Shape Statistics in Mumford-Shah Based Segmentation
We present a variational integration of nonlinear shape statistics into a Mumford?Shah based segmentation process. The nonlinear statistics are derived from a set of training silho...
Christoph Schnörr, Daniel Cremers, Timo Kohlb...
NIPS
2004
13 years 8 months ago
Hierarchical Eigensolver for Transition Matrices in Spectral Methods
We show how to build hierarchical, reduced-rank representation for large stochastic matrices and use this representation to design an efficient algorithm for computing the largest...
Chakra Chennubhotla, Allan D. Jepson