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ML
2002
ACM
178views Machine Learning» more  ML 2002»
15 years 3 months ago
Metric-Based Methods for Adaptive Model Selection and Regularization
We present a general approach to model selection and regularization that exploits unlabeled data to adaptively control hypothesis complexity in supervised learning tasks. The idea ...
Dale Schuurmans, Finnegan Southey
MLDM
2007
Springer
15 years 9 months ago
Transductive Learning from Relational Data
Transduction is an inference mechanism “from particular to particular”. Its application to classification tasks implies the use of both labeled (training) data and unlabeled (...
Michelangelo Ceci, Annalisa Appice, Nicola Barile,...
135
Voted
BMCBI
2008
153views more  BMCBI 2008»
15 years 3 months ago
Improved general regression network for protein domain boundary prediction
Background: Protein domains present some of the most useful information that can be used to understand protein structure and functions. Recent research on protein domain boundary ...
Paul D. Yoo, Abdur R. Sikder, Bing Bing Zhou, Albe...
BIRD
2008
Springer
131views Bioinformatics» more  BIRD 2008»
15 years 5 months ago
Identifying Subcellular Locations from Images of Unknown Resolution
Our group has previously used machine learning techniques to develop computational systems to automatically analyse fluorescence microscope images and classify the location of the ...
Luís Pedro Coelho, Robert F. Murphy
129
Voted
ICMLA
2008
15 years 4 months ago
Mapping Uncharted Waters: Exploratory Analysis, Visualization, and Clustering of Oceanographic Data
In this paper we describe an interdisciplinary collaboration between researchers in machine learning and oceanography. The collaboration was formed to study the problem of open oc...
Joshua M. Lewis, Pincelli M. Hull, Kilian Q. Weinb...