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» Some Theory for Generalized Boosting Algorithms
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AI
2002
Springer
13 years 8 months ago
Ensembling neural networks: Many could be better than all
Neural network ensemble is a learning paradigm where many neural networks are jointly used to solve a problem. In this paper, the relationship between the ensemble and its compone...
Zhi-Hua Zhou, Jianxin Wu, Wei Tang
STOC
2004
ACM
129views Algorithms» more  STOC 2004»
14 years 9 months ago
Sorting and searching in the presence of memory faults (without redundancy)
We investigate the design of algorithms resilient to memory faults, i.e., algorithms that, despite the corruption of some memory values during their execution, are able to produce...
Irene Finocchi, Giuseppe F. Italiano
SPAA
2009
ACM
14 years 3 months ago
Weak graph colorings: distributed algorithms and applications
We study deterministic, distributed algorithms for two weak variants of the standard graph coloring problem. We consider defective colorings, i.e., colorings where nodes of a colo...
Fabian Kuhn
ATAL
2010
Springer
13 years 10 months ago
Parameterizing the winner determination problem for combinatorial auctions
Combinatorial auctions have been studied by the multiagent systems community for some time, since these auctions are an effective mechanism for resource allocation when agents are...
David Loker, Kate Larson
GECCO
2011
Springer
240views Optimization» more  GECCO 2011»
13 years 14 days ago
Collisions are helpful for computing unique input-output sequences
Computing unique input-output sequences (UIOs) from finite state machines (FSMs) is important for conformance testing in software engineering, where evolutionary algorithms (EAs)...
Chao Qian, Yang Yu, Zhi-Hua Zhou