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» Approximate Learning of Dynamic Models
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CIKM
2010
Springer
15 years 3 months ago
Partial drift detection using a rule induction framework
The major challenge in mining data streams is the issue of concept drift, the tendency of the underlying data generation process to change over time. In this paper, we propose a g...
Damon Sotoudeh, Aijun An
ACMSE
2007
ACM
15 years 8 months ago
BehaviorSim: towards an educational tool for behavior-based agent
A major paradigm of modeling the decision making of autonomous agents is through behavior-based network models. The network consists of distributed behaviors that compete (or coop...
Pavel Lakhtanau, Xiaolin Hu, Fasheng Qiu
CORR
2010
Springer
176views Education» more  CORR 2010»
15 years 4 months ago
Sequential item pricing for unlimited supply
We investigate the extent to which price updates can increase the revenue of a seller with little prior information on demand. We study prior-free revenue maximization for a selle...
Maria-Florina Balcan, Florin Constantin
GECCO
2008
Springer
186views Optimization» more  GECCO 2008»
15 years 5 months ago
A pareto following variation operator for fast-converging multiobjective evolutionary algorithms
One of the major difficulties when applying Multiobjective Evolutionary Algorithms (MOEA) to real world problems is the large number of objective function evaluations. Approximate...
A. K. M. Khaled Ahsan Talukder, Michael Kirley, Ra...
ECAI
2010
Springer
15 years 6 months ago
Bayesian Monte Carlo for the Global Optimization of Expensive Functions
In the last decades enormous advances have been made possible for modelling complex (physical) systems by mathematical equations and computer algorithms. To deal with very long run...
Perry Groot, Adriana Birlutiu, Tom Heskes