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AAAI
2006
13 years 9 months ago
Sound and Efficient Inference with Probabilistic and Deterministic Dependencies
Reasoning with both probabilistic and deterministic dependencies is important for many real-world problems, and in particular for the emerging field of statistical relational lear...
Hoifung Poon, Pedro Domingos
SODA
2001
ACM
79views Algorithms» more  SODA 2001»
13 years 9 months ago
Learning Markov networks: maximum bounded tree-width graphs
Markov networks are a common class of graphical models used in machine learning. Such models use an undirected graph to capture dependency information among random variables in a ...
David R. Karger, Nathan Srebro
WWW
2003
ACM
14 years 8 months ago
Mining topic-specific concepts and definitions on the web
Traditionally, when one wants to learn about a particular topic, one reads a book or a survey paper. With the rapid expansion of the Web, learning in-depth knowledge about a topic...
Bing Liu, Chee Wee Chin, Hwee Tou Ng
ICCV
2009
IEEE
15 years 15 days ago
TagProp: Discriminative Metric Learning in Nearest Neighbor Models for Image Auto-Annotation
Image auto-annotation is an important open problem in computer vision. For this task we propose TagProp, a discriminatively trained nearest neighbor model. Tags of test images a...
Matthieu Guillaumin, Thomas Mensink, Jakob Verbeek...
WIKIS
2006
ACM
14 years 1 months ago
How to use a Wiki in education: 'Wiki based effective constructive learning'
Learning effectiveness depends on a large range of parameters. Learners’ activity has an important impact on long-term learning and comprehension of difficult concepts [1]. Coll...
Michele Notari