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JMLR
2006
118views more  JMLR 2006»
13 years 7 months ago
Learning Factor Graphs in Polynomial Time and Sample Complexity
We study the computational and sample complexity of parameter and structure learning in graphical models. Our main result shows that the class of factor graphs with bounded degree...
Pieter Abbeel, Daphne Koller, Andrew Y. Ng
CVPR
2012
IEEE
11 years 10 months ago
Geodesic flow kernel for unsupervised domain adaptation
In real-world applications of visual recognition, many factors—such as pose, illumination, or image quality—can cause a significant mismatch between the source domain on whic...
Boqing Gong, Yuan Shi, Fei Sha, Kristen Grauman
CONEXT
2006
ACM
14 years 1 months ago
Synergy: blending heterogeneous measurement elements for effective network monitoring
Network traffic matrices are important for various network planning and management operations. Previous work for estimation of traffic matrices is based on either link load record...
Awais Ahmed Awan, Andrew W. Moore
KI
2002
Springer
13 years 7 months ago
Advantages, Opportunities and Limits of Empirical Evaluations: Evaluating Adaptive Systems
While empirical evaluations are a common research method in some areas of Artificial Intelligence (AI), others still neglect this approach. This article outlines both the opportun...
Stephan Weibelzahl, Gerhard Weber
CVPR
2010
IEEE
13 years 5 months ago
Adaptive pose priors for pictorial structures
Pictorial structure (PS) models are extensively used for part-based recognition of scenes, people, animals and multi-part objects. To achieve tractability, the structure and param...
Benjamin Sapp, Chris Jordan, Ben Taskar