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ML
2010
ACM
135views Machine Learning» more  ML 2010»
14 years 9 months ago
Multi-domain learning by confidence-weighted parameter combination
State-of-the-art statistical NLP systems for a variety of tasks learn from labeled training data that is often domain specific. However, there may be multiple domains or sources o...
Mark Dredze, Alex Kulesza, Koby Crammer
NIPS
2000
15 years 4 months ago
Active Learning for Parameter Estimation in Bayesian Networks
Bayesian networks are graphical representations of probability distributions. In virtually all of the work on learning these networks, the assumption is that we are presented with...
Simon Tong, Daphne Koller
BMCBI
2010
118views more  BMCBI 2010»
15 years 3 months ago
From learning taxonomies to phylogenetic learning: Integration of 16S rRNA gene data into FAME-based bacterial classification
Background: Machine learning techniques have shown to improve bacterial species classification based on fatty acid methyl ester (FAME) data. Nonetheless, FAME analysis has a limit...
Bram Slabbinck, Willem Waegeman, Peter Dawyndt, Pa...
ICCS
2001
Springer
15 years 7 months ago
Distributed Name Service in Harness
Abstract. The Harness metacomputing framework is a reliable and flexible environment for distributed computing. A shortcoming of the system is that services are dependent on a nam...
Tomasz Tyrakowski, Vaidy S. Sunderam, Mauro Miglia...
ICIP
2008
IEEE
16 years 4 months ago
Implicit spatial inference with sparse local features
This paper introduces a novel way to leverage the implicit geometry of sparse local features (e.g. SIFT operator) for the purposes of object detection and segmentation. A two-clas...
Deirdre O'Regan, Anil C. Kokaram