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» Information Theory, Inference, and Learning Algorithms
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AI
2000
Springer
13 years 7 months ago
Learning to construct knowledge bases from the World Wide Web
The World Wide Web is a vast source of information accessible to computers, but understandable only to humans. The goal of the research described here is to automatically create a...
Mark Craven, Dan DiPasquo, Dayne Freitag, Andrew M...
CHI
2011
ACM
12 years 11 months ago
Apolo: making sense of large network data by combining rich user interaction and machine learning
Extracting useful knowledge from large network datasets has become a fundamental challenge in many domains, from scientific literature to social networks and the web. We introduc...
Duen Horng Chau, Aniket Kittur, Jason I. Hong, Chr...
WACV
2002
IEEE
14 years 27 days ago
Range Synthesis for 3D Environment Modeling
In this paper a range synthesis algorithm is proposed as an initial solution to the problem of 3D environment modeling from sparse data. We develop a statistical learning method f...
Luz Abril Torres-Méndez, Gregory Dudek
AI
2002
Springer
13 years 7 months ago
Learning Bayesian networks from data: An information-theory based approach
This paper provides algorithms that use an information-theoretic analysis to learn Bayesian network structures from data. Based on our three-phase learning framework, we develop e...
Jie Cheng, Russell Greiner, Jonathan Kelly, David ...
KDD
2005
ACM
158views Data Mining» more  KDD 2005»
14 years 8 months ago
Adversarial learning
Many classification tasks, such as spam filtering, intrusion detection, and terrorism detection, are complicated by an adversary who wishes to avoid detection. Previous work on ad...
Daniel Lowd, Christopher Meek