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NIPS
2008
15 years 8 months ago
Learning Taxonomies by Dependence Maximization
We introduce a family of unsupervised algorithms, numerical taxonomy clustering, to simultaneously cluster data, and to learn a taxonomy that encodes the relationship between the ...
Matthew B. Blaschko, Arthur Gretton
SDM
2007
SIAM
133views Data Mining» more  SDM 2007»
15 years 8 months ago
Change-Point Detection using Krylov Subspace Learning
We propose an efficient algorithm for principal component analysis (PCA) that is applicable when only the inner product with a given vector is needed. We show that Krylov subspace...
Tsuyoshi Idé, Koji Tsuda
NIPS
2003
15 years 8 months ago
Learning a Distance Metric from Relative Comparisons
This paper presents a method for learning a distance metric from relative comparison such as “A is closer to B than A is to C”. Taking a Support Vector Machine (SVM) approach,...
Matthew Schultz, Thorsten Joachims
CACM
2000
125views more  CACM 2000»
15 years 6 months ago
All I Really Need to Know About Pair Programming I Learned in Kindergarten
All I Really Need to Know I Learned in Kindergarten By Robert Fulghum (Fulghum 1988) Share everything. Play fair. Don't hit people. Put things back where you found them. Clea...
Laurie A. Williams, Robert R. Kessler
EMNLP
2010
15 years 4 months ago
Cross Language Text Classification by Model Translation and Semi-Supervised Learning
In this paper, we introduce a method that automatically builds text classifiers in a new language by training on already labeled data in another language. Our method transfers the...
Lei Shi, Rada Mihalcea, Mingjun Tian