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» Machine learning in sedimentation modelling
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ICML
2005
IEEE
14 years 10 months ago
Active learning for Hidden Markov Models: objective functions and algorithms
Hidden Markov Models (HMMs) model sequential data in many fields such as text/speech processing and biosignal analysis. Active learning algorithms learn faster and/or better by cl...
Brigham Anderson, Andrew Moore
ACL
2004
13 years 11 months ago
Applying Machine Learning to Chinese Temporal Relation Resolution
Temporal relation resolution involves extraction of temporal information explicitly or implicitly embedded in a language. This information is often inferred from a variety of inte...
Wenjie Li, Kam-Fai Wong, Guihong Cao, Chunfa Yuan
ECML
2006
Springer
14 years 1 months ago
Transductive Gaussian Process Regression with Automatic Model Selection
Abstract. In contrast to the standard inductive inference setting of predictive machine learning, in real world learning problems often the test instances are already available at ...
Quoc V. Le, Alexander J. Smola, Thomas Gärtne...
MICCAI
2007
Springer
14 years 10 months ago
Active-Contour-Based Image Segmentation Using Machine Learning Techniques
Abstract. We introduce a non-linear shape prior for the deformable model framework that we learn from a set of shape samples using recent manifold learning techniques. We model a c...
Patrick Etyngier, Florent Ségonne, Renaud K...
MICCAI
2008
Springer
14 years 11 months ago
Classification of Suspected Liver Metastases Using fMRI Images: A Machine Learning Approach
Abstract. This paper presents a machine-learning approach to the interactive classification of suspected liver metastases in fMRI images. The method uses fMRI-based statistical mod...
Moti Freiman, Yifat Edrei, Yehonatan Sela, Yitz...