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» Learning to Identify Unexpected Instances in the Test Set
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NIPS
2007
13 years 8 months ago
Predicting Brain States from fMRI Data: Incremental Functional Principal Component Regression
We propose a method for reconstruction of human brain states directly from functional neuroimaging data. The method extends the traditional multivariate regression analysis of dis...
Sennay Ghebreab, Arnold W. M. Smeulders, Pieter W....
ADMA
2010
Springer
271views Data Mining» more  ADMA 2010»
13 years 2 months ago
Exploiting Concept Clumping for Efficient Incremental E-Mail Categorization
We introduce a novel approach to incremental e-mail categorization based on identifying and exploiting "clumps" of messages that are classified similarly. Clumping reflec...
Alfred Krzywicki, Wayne Wobcke
CORR
2012
Springer
184views Education» more  CORR 2012»
12 years 3 months ago
Noisy-OR Models with Latent Confounding
Given a set of experiments in which varying subsets of observed variables are subject to intervention, we consider the problem of identifiability of causal models exhibiting late...
Antti Hyttinen, Frederick Eberhardt, Patrik O. Hoy...
SIGSOFT
2009
ACM
14 years 8 months ago
Automatic steering of behavioral model inference
Many testing and analysis techniques use finite state models to validate and verify the quality of software systems. Since the specification of such models is complex and timecons...
David Lo, Leonardo Mariani, Mauro Pezzè
BMCBI
2005
134views more  BMCBI 2005»
13 years 7 months ago
Systematic feature evaluation for gene name recognition
In task 1A of the BioCreAtIvE evaluation, systems had to be devised that recognize words and phrases forming gene or protein names in natural language sentences. We approach this ...
Jörg Hakenberg, Steffen Bickel, Conrad Plake,...