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NIPS
2004
13 years 9 months ago
Multiple Relational Embedding
We describe a way of using multiple different types of similarity relationship to learn a low-dimensional embedding of a dataset. Our method chooses different, possibly overlappin...
Roland Memisevic, Geoffrey E. Hinton
NIPS
2003
13 years 9 months ago
Fast Feature Selection from Microarray Expression Data via Multiplicative Large Margin Algorithms
New feature selection algorithms for linear threshold functions are described which combine backward elimination with an adaptive regularization method. This makes them particular...
Claudio Gentile
BMCBI
2006
79views more  BMCBI 2006»
13 years 8 months ago
The effects of multiple features of alternatively spliced exons on the KA/KS ratio test
Background: The evolution of alternatively spliced exons (ASEs) is of primary interest because these exons are suggested to be a major source of functional diversity of proteins. ...
Feng-Chi Chen, Trees-Juen Chuang
TCAD
1998
154views more  TCAD 1998»
13 years 7 months ago
Address generation for memories containing multiple arrays
This paper presents techniques for generating addresses for memories containing multiple arrays. Because these techniques rely on the inversion or rearrangement of address bits, t...
Herman Schmit, Donald E. Thomas
SCHEDULING
2010
59views more  SCHEDULING 2010»
13 years 6 months ago
Implicit shift scheduling with multiple breaks and work stretch duration restrictions
This paper considers a shift scheduling problem that includes different forms of flexibility in terms of shift starting times, break lengths and break placement. Two particular ...
Monia Rekik, Jean-François Cordeau, Fran&cc...