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» Neural networks: Algorithms and applications
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GECCO
2006
Springer
208views Optimization» more  GECCO 2006»
15 years 11 months ago
Comparing evolutionary and temporal difference methods in a reinforcement learning domain
Both genetic algorithms (GAs) and temporal difference (TD) methods have proven effective at solving reinforcement learning (RL) problems. However, since few rigorous empirical com...
Matthew E. Taylor, Shimon Whiteson, Peter Stone
IJCAI
2007
15 years 9 months ago
Constructing New and Better Evaluation Measures for Machine Learning
Evaluation measures play an important role in machine learning because they are used not only to compare different learning algorithms, but also often as goals to optimize in cons...
Jin Huang, Charles X. Ling
AAAI
2004
15 years 9 months ago
Online Parallel Boosting
This paper presents a new boosting (arcing) algorithm called POCA, Parallel Online Continuous Arcing. Unlike traditional boosting algorithms (such as Arc-x4 and Adaboost), that co...
Jesse A. Reichler, Harlan D. Harris, Michael A. Sa...
ANOR
2010
130views more  ANOR 2010»
15 years 5 months ago
Greedy scheduling with custom-made objectives
We present a methodology to automatically generate an online job scheduling method for a custom-made objective and real workloads. The scheduling problem comprises independent para...
Carsten Franke, Joachim Lepping, Uwe Schwiegelshoh...
HICSS
2003
IEEE
88views Biometrics» more  HICSS 2003»
16 years 27 days ago
Expanding Citizen Access and Public Official Accountability through Knowledge Creation Technology: One Recent Development in e-D
The authors describe an addition to the conversation regarding enhanced democracy through technologicallyassisted means (e-Democracy) focusing on enhancing and expanding the typic...
Michael A. Shires, Murray S. Craig