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» Active Learning with Model Selection in Linear Regression
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ICIP
2007
IEEE
14 years 19 days ago
Unsupervised Nonlinear Manifold Learning
This communication deals with data reduction and regression. A set of high dimensional data (e.g., images) usually has only a few degrees of freedom with corresponding variables t...
Matthieu Brucher, Christian Heinrich, Fabrice Heit...
BMCBI
2007
174views more  BMCBI 2007»
13 years 9 months ago
Inferring activity changes of transcription factors by binding association with sorted expression profiles
Background: The identification of transcription factors (TFs) associated with a biological process is fundamental to understanding its regulatory mechanisms. From microarray data,...
Chao Cheng, Xiting Yan, Fengzhu Sun, Lei M. Li
ENTCS
2007
156views more  ENTCS 2007»
13 years 8 months ago
Bounded Model Checking with Parametric Data Structures
Bounded Model Checking (BMC) is a successful refutation method to detect errors in not only circuits and other binary systems but also in systems with more complex domains like ti...
Erika Ábrahám, Marc Herbstritt, Bern...
COGSCI
2007
85views more  COGSCI 2007»
13 years 8 months ago
Semantic Boost on Episodic Associations: An Empirically-Based Computational Model
Words become associated following repeated co-occurrence episodes. This process might be further determined by the semantic characteristics of the words. The present study focused...
Yaron Silberman, Shlomo Bentin, Risto Miikkulainen
CORR
2011
Springer
192views Education» more  CORR 2011»
13 years 3 months ago
Distribution-Independent Evolvability of Linear Threshold Functions
Valiant’s (2007) model of evolvability models the evolutionary process of acquiring useful functionality as a restricted form of learning from random examples. Linear threshold ...
Vitaly Feldman