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» Machine learning problems from optimization perspective
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139
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JMLR
2008
209views more  JMLR 2008»
15 years 2 months ago
Bayesian Inference and Optimal Design for the Sparse Linear Model
The linear model with sparsity-favouring prior on the coefficients has important applications in many different domains. In machine learning, most methods to date search for maxim...
Matthias W. Seeger
EUROGP
2000
Springer
15 years 5 months ago
Seeding Genetic Programming Populations
We show genetic programming (GP) populations can evolve under the influence of a Pareto multi-objective fitness and program size selection scheme, from "perfect" programs...
William B. Langdon, Peter Nordin
BMCBI
2005
155views more  BMCBI 2005»
15 years 2 months ago
Mining protein function from text using term-based support vector machines
Background: Text mining has spurred huge interest in the domain of biology. The goal of the BioCreAtIvE exercise was to evaluate the performance of current text mining systems. We...
Simon B. Rice, Goran Nenadic, Benjamin J. Stapley
149
Voted
ICML
2005
IEEE
16 years 3 months ago
Efficient discriminative learning of Bayesian network classifier via boosted augmented naive Bayes
The use of Bayesian networks for classification problems has received significant recent attention. Although computationally efficient, the standard maximum likelihood learning me...
Yushi Jing, Vladimir Pavlovic, James M. Rehg
132
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AIME
2009
Springer
14 years 11 months ago
Segmentation of Lung Tumours in Positron Emission Tomography Scans: A Machine Learning Approach
Lung cancer represents the most deadly type of malignancy. In this work we propose a machine learning approach to segmenting lung tumours in Positron Emission Tomography (PET) scan...
Aliaksei Kerhet, Cormac Small, Harvey Quon, Terenc...