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JMLR
2010
149views more  JMLR 2010»
14 years 9 months ago
Learning Bayesian Network Structure using LP Relaxations
We propose to solve the combinatorial problem of finding the highest scoring Bayesian network structure from data. This structure learning problem can be viewed as an inference pr...
Tommi Jaakkola, David Sontag, Amir Globerson, Mari...
128
Voted
ICCV
2007
IEEE
16 years 4 months ago
Learning Structured Appearance Models from Captioned Images of Cluttered Scenes
Given an unstructured collection of captioned images of cluttered scenes featuring a variety of objects, our goal is to learn both the names and appearances of the objects. Only a...
Michael Jamieson, Afsaneh Fazly, Sven J. Dickinson...
KDD
2005
ACM
145views Data Mining» more  KDD 2005»
16 years 2 months ago
Using and Learning Semantics in Frequent Subgraph Mining
The search for frequent subgraphs is becoming increasingly important in many application areas including Web mining and bioinformatics. Any use of graph structures in mining, howev...
Bettina Berendt
MSR
2005
ACM
15 years 8 months ago
Mining version histories to verify the learning process of Legitimate Peripheral Participants
Since code revisions reflect the extent of human involvement in the software development process, revision histories reveal the interactions and interfaces between developers and...
Shih-Kun Huang, Kang-min Liu
131
Voted
IJCAI
1997
15 years 3 months ago
Machine Learning Techniques to Make Computers Easier to Use
Identifying user-dependent information that can be automatically collected helps build a user model by which 1) to predict what the user wants to do next and 2) to do relevant pre...
Hiroshi Motoda, Kenichi Yoshida