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» Semi-Supervised Learning with Trees
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AI
2006
Springer
13 years 8 months ago
Controlled generation of hard and easy Bayesian networks: Impact on maximal clique size in tree clustering
This article presents and analyzes algorithms that systematically generate random Bayesian networks of varying difficulty levels, with respect to inference using tree clustering. ...
Ole J. Mengshoel, David C. Wilkins, Dan Roth
ACL
2010
13 years 6 months ago
Blocked Inference in Bayesian Tree Substitution Grammars
Learning a tree substitution grammar is very challenging due to derivational ambiguity. Our recent approach used a Bayesian non-parametric model to induce good derivations from tr...
Trevor Cohn, Phil Blunsom
CAV
2011
Springer
216views Hardware» more  CAV 2011»
12 years 11 months ago
Malware Analysis with Tree Automata Inference
Abstract. The underground malware-based economy is flourishing and it is evident that the classical ad-hoc signature detection methods are becoming insufficient. Malware authors ...
Domagoj Babic, Daniel Reynaud, Dawn Song
AINA
2006
IEEE
14 years 2 months ago
Peer-Tree: A Hybrid Peer-to-Peer Overlay for Service Discovery
Efficient service discovery in dynamic, crossorganizational VO is one of the challenge aspects in ChinaGrid. Network overlay and search algorithms are two important considerations...
Jing Tie, Hai Jin, Shengli Li, Xuanhua Shi, Hanhua...
UAI
2004
13 years 9 months ago
Dynamical Systems Trees
We propose dynamical systems trees (DSTs) as a flexible model for describing multiple processes that interact via a hierarchy of aggregating processes. DSTs extend nonlinear dynam...
Andrew Howard, Tony Jebara