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NIPS
2003
15 years 8 months ago
Multiple-Instance Learning via Disjunctive Programming Boosting
Learning from ambiguous training data is highly relevant in many applications. We present a new learning algorithm for classification problems where labels are associated with se...
Stuart Andrews, Thomas Hofmann
JAIR
2008
136views more  JAIR 2008»
15 years 6 months ago
Global Inference for Sentence Compression: An Integer Linear Programming Approach
Sentence compression holds promise for many applications ranging from summarization to subtitle generation. Our work views sentence compression as an optimization problem and uses...
James Clarke, Mirella Lapata
CIDM
2007
IEEE
16 years 1 months ago
Reactive Query Policies: A Formalism for Planning with Volatile External Information
— To generate plans for collecting data for data mining, an important problem is information volatility during planning: the information needed by the planning system may change ...
Tsz-Chiu Au, Dana S. Nau
177
Voted
IJCNN
2006
IEEE
16 years 23 days ago
Shaping Realistic Neuronal Morphologies: An Evolutionary Computation Method
— Neuronal morphology plays a crucial role in the information processing capabilities of neurons. Despite the importance of morphology for neural functionality, biological data i...
Ben Torben-Nielsen, Karl Tuyls, Eric O. Postma
EMO
2006
Springer
172views Optimization» more  EMO 2006»
15 years 10 months ago
Steady-State Selection and Efficient Covariance Matrix Update in the Multi-objective CMA-ES
The multi-objective covariance matrix adaptation evolution strategy (MO-CMA-ES) combines a mutation operator that adapts its search distribution to the underlying optimization prob...
Christian Igel, Thorsten Suttorp, Nikolaus Hansen