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» Learning Algorithms for Domain Adaptation
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FLAIRS
2004
13 years 8 months ago
A Method Based on RBF-DDA Neural Networks for Improving Novelty Detection in Time Series
Novelty detection in time series is an important problem with application in different domains such as machine failure detection, fraud detection and auditing. An approach to this...
Adriano L. I. Oliveira, Fernando Buarque de Lima N...
NIPS
2003
13 years 8 months ago
Max-Margin Markov Networks
In typical classification tasks, we seek a function which assigns a label to a single object. Kernel-based approaches, such as support vector machines (SVMs), which maximize the ...
Benjamin Taskar, Carlos Guestrin, Daphne Koller
BMCBI
2010
171views more  BMCBI 2010»
13 years 7 months ago
PyMix - The Python mixture package - a tool for clustering of heterogeneous biological data
Background: Cluster analysis is an important technique for the exploratory analysis of biological data. Such data is often high-dimensional, inherently noisy and contains outliers...
Benjamin Georgi, Ivan Gesteira Costa, Alexander Sc...
BMCBI
2008
112views more  BMCBI 2008»
13 years 7 months ago
A simplified approach to disulfide connectivity prediction from protein sequences
Background: Prediction of disulfide bridges from protein sequences is useful for characterizing structural and functional properties of proteins. Several methods based on differen...
Marc Vincent, Andrea Passerini, Matthieu Labb&eacu...
AIM
2005
13 years 7 months ago
Semantic Integration in Text: From Ambiguous Names to Identifiable Entities
Intelligent access to information requires semantic integration of structured databases with unstructured textual resources. While the semantic integration problem has been widely...
Xin Li, Paul Morie, Dan Roth