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» Analysing Randomized Distributed Algorithms
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ICML
2007
IEEE
16 years 5 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
TEC
2012
234views Formal Methods» more  TEC 2012»
13 years 7 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
NIPS
2004
15 years 6 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
KCAP
2011
ACM
14 years 7 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 5 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