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» Analysing Randomized Distributed Algorithms
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134
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ICML
2007
IEEE
16 years 3 months ago
Combining online and offline knowledge in UCT
The UCT algorithm learns a value function online using sample-based search. The TD() algorithm can learn a value function offline for the on-policy distribution. We consider three...
Sylvain Gelly, David Silver
171
Voted
TEC
2012
234views Formal Methods» more  TEC 2012»
13 years 4 months ago
Cooperatively Coevolving Particle Swarms for Large Scale Optimization
—This paper presents a new cooperative coevolving particle swarm optimization (CCPSO) algorithm in an attempt to address the issue of scaling up particle swarm optimization (PSO)...
Xiaodong Li, Xin Yao
148
Voted
NIPS
2004
15 years 3 months ago
Co-Training and Expansion: Towards Bridging Theory and Practice
Co-training is a method for combining labeled and unlabeled data when examples can be thought of as containing two distinct sets of features. It has had a number of practical succ...
Maria-Florina Balcan, Avrim Blum, Ke Yang
156
Voted
KCAP
2011
ACM
14 years 5 months ago
LinkedDataLens: linked data as a network of networks
With billions of assertions and counting, the Web of Data represents the largest multi-contributor interlinked knowledge base that ever existed. We present a novel framework for a...
Yolanda Gil, Paul T. Groth
ICML
2006
IEEE
16 years 3 months ago
An analysis of graph cut size for transductive learning
I consider the setting of transductive learning of vertex labels in graphs, in which a graph with n vertices is sampled according to some unknown distribution; there is a true lab...
Steve Hanneke