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ML
2008
ACM
110views Machine Learning» more  ML 2008»
15 years 3 months ago
A theory of learning with similarity functions
Kernel functions have become an extremely popular tool in machine learning, with an attractive theory as well. This theory views a kernel as implicitly mapping data points into a ...
Maria-Florina Balcan, Avrim Blum, Nathan Srebro
VISSYM
2003
15 years 6 months ago
Visual Hierarchical Dimension Reduction for Exploration of High Dimensional Datasets
Traditional visualization techniques for multidimensional data sets, such as parallel coordinates, glyphs, and scatterplot matrices, do not scale well to high numbers of dimension...
Jing Yang, Matthew O. Ward, Elke A. Rundensteiner,...
BMCBI
2006
207views more  BMCBI 2006»
15 years 4 months ago
A new measure for functional similarity of gene products based on Gene Ontology
Background: Gene Ontology (GO) is a standard vocabulary of functional terms and allows for coherent annotation of gene products. These annotations provide a basis for new methods ...
Andreas Schlicker, Francisco S. Domingues, Jö...
SIGMOD
2010
ACM
324views Database» more  SIGMOD 2010»
15 years 9 months ago
Similarity search and locality sensitive hashing using ternary content addressable memories
Similarity search methods are widely used as kernels in various data mining and machine learning applications including those in computational biology, web search/clustering. Near...
Rajendra Shinde, Ashish Goel, Pankaj Gupta, Debojy...
157
Voted
ACL
1992
15 years 5 months ago
SEXTANT: Exploring Unexplored Contexts for Semantic Extraction from Syntactic Analysis
For a very long time, it has been considered that the only way of automatically extracting similar groups of words from a text collection for which no semantic information exists ...
Gregory Grefenstette