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» Machine Learning with Data Dependent Hypothesis Classes
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ICML
2004
IEEE
14 years 9 months ago
Dynamic conditional random fields: factorized probabilistic models for labeling and segmenting sequence data
In sequence modeling, we often wish to represent complex interaction between labels, such as when performing multiple, cascaded labeling tasks on the same sequence, or when longra...
Charles A. Sutton, Khashayar Rohanimanesh, Andrew ...
BICOB
2010
Springer
13 years 6 months ago
Multiple Kernel Learning for Fold Recognition
Fold recognition is a key problem in computational biology that involves classifying protein sharing structural similarities into classes commonly known as "folds". Rece...
Huzefa Rangwala
TSMC
2008
136views more  TSMC 2008»
13 years 8 months ago
Learning Relational Descriptions of Differentially Expressed Gene Groups
Abstract-- This paper presents a method that uses gene ontologies, together with the paradigm of relational subgroup discovery, to find compactly described groups of genes differen...
Igor Trajkovski, Filip Zelezný, Nada Lavrac...
AIA
2007
13 years 10 months ago
A framework for generating data to simulate changing environments
A fundamental assumption often made in supervised classification is that the problem is static, i.e. the description of the classes does not change with time. However many practi...
Anand M. Narasimhamurthy, Ludmila I. Kuncheva
AIPR
2003
IEEE
14 years 13 days ago
Sensor and Classifier Fusion for Outdoor Obstacle Detection: an Application of Data Fusion To Autonomous Off-Road Navigation
This paper describes an approach for using several levels of data fusion in the domain of autonomous off-road navigation. We are focusing on outdoor obstacle detection, and we pre...
Cristian Dima, Nicolas Vandapel, Martial Hebert