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ICML
2005
IEEE
16 years 4 months ago
Clustering through ranking on manifolds
Clustering aims to find useful hidden structures in data. In this paper we present a new clustering algorithm that builds upon the consistency method (Zhou, et.al., 2003), a semi-...
Markus Breitenbach, Gregory Z. Grudic
ECML
2007
Springer
15 years 9 months ago
Spectral Clustering and Embedding with Hidden Markov Models
Abstract. Clustering has recently enjoyed progress via spectral methods which group data using only pairwise affinities and avoid parametric assumptions. While spectral clustering ...
Tony Jebara, Yingbo Song, Kapil Thadani
130
Voted
MICRO
1998
IEEE
91views Hardware» more  MICRO 1998»
15 years 7 months ago
Effective Cluster Assignment for Modulo Scheduling
Clustering is one solution to the demand for wideissue machines and fast clock cycles because it allows for smaller, less ported register files and simpler bypass logic while rema...
Erik Nystrom, Alexandre E. Eichenberger
146
Voted
ECML
2006
Springer
15 years 7 months ago
An Adaptive Kernel Method for Semi-supervised Clustering
Semi-supervised clustering uses the limited background knowledge to aid unsupervised clustering algorithms. Recently, a kernel method for semi-supervised clustering has been introd...
Bojun Yan, Carlotta Domeniconi
CLEF
2010
Springer
15 years 4 months ago
MapReduce for Information Retrieval Evaluation: "Let's Quickly Test This on 12 TB of Data"
We propose to use MapReduce to quickly test new retrieval approaches on a cluster of machines by sequentially scanning all documents. We present a small case study in which we use ...
Djoerd Hiemstra, Claudia Hauff