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126
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PPSN
2010
Springer
14 years 10 months ago
Feature Selection for Multi-purpose Predictive Models: A Many-Objective Task
The target of machine learning is a predictive model that performs well on unseen data. Often, such a model has multiple intended uses, related to different points in the tradeoff ...
Alan P. Reynolds, David W. Corne, Michael J. Chant...
97
Voted
ICML
2005
IEEE
16 years 1 months ago
Semi-supervised graph clustering: a kernel approach
Semi-supervised clustering algorithms aim to improve clustering results using limited supervision. The supervision is generally given as pairwise constraints; such constraints are...
Brian Kulis, Sugato Basu, Inderjit S. Dhillon, Ray...
COLT
2008
Springer
15 years 2 months ago
Linear Algorithms for Online Multitask Classification
We design and analyze interacting online algorithms for multitask classification that perform better than independent learners whenever the tasks are related in a certain sense. W...
Giovanni Cavallanti, Nicolò Cesa-Bianchi, C...
109
Voted
ECTEL
2009
Springer
15 years 4 months ago
The Influence of Coalition Formation on Idea Selection in Dispersed Teams: A Game Theoretic Approach
In an open innovation environment, organizational learning takes place by means of dispersed teams which expand their knowledge through collaborative idea generation. Research is o...
Rory L. L. Sie, Marlies Bitter-Rijpkema, Peter B. ...
96
Voted
ICML
2009
IEEE
16 years 1 months ago
Learning Markov logic network structure via hypergraph lifting
Markov logic networks (MLNs) combine logic and probability by attaching weights to first-order clauses, and viewing these as templates for features of Markov networks. Learning ML...
Stanley Kok, Pedro Domingos