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15 years 1 months ago
A Probabilistic Learning Approach to Whole-Genome Operon Prediction
We present a computational approach to predicting operons in the genomes of prokaryotic organisms. Our approach uses machine learning methods to induce predictive models for this ...
Mark Craven, David Page, Jude W. Shavlik, Joseph B...
LREC
2008
103views Education» more  LREC 2008»
15 years 1 months ago
From Field Notes towards a Knowledge Base
We describe the process of converting plain text cultural heritage data to elements of a domain-specific knowledge base, using general machine learning techniques. First, digitise...
Piroska Lendvai, Steve Hunt
CVPR
2012
IEEE
13 years 2 months ago
From pixels to physics: Probabilistic color de-rendering
Consumer digital cameras use tone-mapping to produce compact, narrow-gamut images that are nonetheless visually pleasing. In doing so, they discard or distort substantial radiomet...
Ying Xiong, Kate Saenko, Trevor Darrell, Todd Zick...
CVIU
2006
110views more  CVIU 2006»
14 years 12 months ago
Simultaneous tracking of multiple body parts of interacting persons
This paper presents a framework to simultaneously segment and track multiple body parts of interacting humans in the presence of mutual occlusion and shadow. The framework uses mu...
Sangho Park, Jake K. Aggarwal
ICML
2008
IEEE
16 years 19 days ago
Composite kernel learning
The Support Vector Machine (SVM) is an acknowledged powerful tool for building classifiers, but it lacks flexibility, in the sense that the kernel is chosen prior to learning. Mul...
Marie Szafranski, Yves Grandvalet, Alain Rakotomam...