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BMCBI
2007
178views more  BMCBI 2007»
15 years 6 months ago
SVM clustering
Background: Support Vector Machines (SVMs) provide a powerful method for classification (supervised learning). Use of SVMs for clustering (unsupervised learning) is now being cons...
Stephen Winters-Hilt, Sam Merat
ECCC
2010
89views more  ECCC 2010»
15 years 6 months ago
Estimating the unseen: A sublinear-sample canonical estimator of distributions
We introduce a new approach to characterizing the unobserved portion of a distribution, which provides sublinear-sample additive estimators for a class of properties that includes...
Gregory Valiant, Paul Valiant
ICDE
2007
IEEE
185views Database» more  ICDE 2007»
16 years 7 months ago
On k-Nearest Neighbor Searching in Non-Ordered Discrete Data Spaces
A k-nearest neighbor (k-NN) query retrieves k objects from a database that are considered to be the closest to a given query point. Numerous techniques have been proposed in the p...
Dashiell Kolbe, Qiang Zhu, Sakti Pramanik
NIPS
2003
15 years 7 months ago
Max-Margin Markov Networks
In typical classification tasks, we seek a function which assigns a label to a single object. Kernel-based approaches, such as support vector machines (SVMs), which maximize the ...
Benjamin Taskar, Carlos Guestrin, Daphne Koller
191
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BMCBI
2010
243views more  BMCBI 2010»
15 years 6 months ago
Comparative study of unsupervised dimension reduction techniques for the visualization of microarray gene expression data
Background: Visualization of DNA microarray data in two or three dimensional spaces is an important exploratory analysis step in order to detect quality issues or to generate new ...
Christoph Bartenhagen, Hans-Ulrich Klein, Christia...