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» An empirical study of optimizations in YOGI
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ECAI
2004
Springer
14 years 1 months ago
Towards Efficient Learning of Neural Network Ensembles from Arbitrarily Large Datasets
Advances in data collection technologies allow accumulation of large and high dimensional datasets and provide opportunities for learning high quality classification and regression...
Kang Peng, Zoran Obradovic, Slobodan Vucetic
ECML
2004
Springer
13 years 11 months ago
Naive Bayesian Classifiers for Ranking
It is well-known that naive Bayes performs surprisingly well in classification, but its probability estimation is poor. In many applications, however, a ranking based on class prob...
Harry Zhang, Jiang Su
CEC
2005
IEEE
13 years 9 months ago
Multi-objective optimisation of the pump scheduling problem using SPEA2
Abstract- Significant operational cost and energy savings can be achieved by optimising the schedules of pumps, which pump water from source reservoirs to storage tanks, in Water ...
Manuel López-Ibáñez, T. Devi ...
ATAL
2010
Springer
13 years 9 months ago
Quasi deterministic POMDPs and DecPOMDPs
In this paper, we study a particular subclass of partially observable models, called quasi-deterministic partially observable Markov decision processes (QDET-POMDPs), characterize...
Camille Besse, Brahim Chaib-draa
ML
2008
ACM
101views Machine Learning» more  ML 2008»
13 years 7 months ago
On reoptimizing multi-class classifiers
Significant changes in the instance distribution or associated cost function of a learning problem require one to reoptimize a previously-learned classifier to work under new cond...
Chris Bourke, Kun Deng, Stephen D. Scott, Robert E...