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ECML
1993
Springer
15 years 5 months ago
Exploiting Context When Learning to Classify
This paper addresses the problem of classifying observations when features are context-sensitive, specifically when the testing set involves a context that is different from the t...
Peter D. Turney
AI
2006
Springer
15 years 5 months ago
A Classification-Based Glioma Diffusion Model Using MRI Data
Gliomas are diffuse, invasive brain tumors. We propose a 3D classification-based diffusion model, cdm, that predicts how a glioma will grow at a voxel-level, on the basis of featur...
Marianne Morris, Russell Greiner, Jörg Sander...
NIPS
2003
15 years 2 months ago
Gaussian Process Latent Variable Models for Visualisation of High Dimensional Data
In this paper we introduce a new underlying probabilistic model for principal component analysis (PCA). Our formulation interprets PCA as a particular Gaussian process prior on a ...
Neil D. Lawrence
ISSTA
2012
ACM
13 years 4 months ago
Residual investigation: predictive and precise bug detection
We introduce the concept of “residual investigation” for program analysis. A residual investigation is a dynamic check installed as a result of running a static analysis that ...
Kaituo Li, Christoph Reichenbach, Christoph Csalln...
ICASSP
2010
IEEE
15 years 1 months ago
Semi-Supervised Fisher Linear Discriminant (SFLD)
Supervised learning uses a training set of labeled examples to compute a classifier which is a mapping from feature vectors to class labels. The success of a learning algorithm i...
Seda Remus, Carlo Tomasi