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107
Voted
ICML
2007
IEEE
16 years 3 months ago
Parameter learning for relational Bayesian networks
We present a method for parameter learning in relational Bayesian networks (RBNs). Our approach consists of compiling the RBN model into a computation graph for the likelihood fun...
Manfred Jaeger
134
Voted
FUZZIEEE
2007
IEEE
15 years 9 months ago
Learning Undirected Possibilistic Networks with Conditional Independence Tests
—Approaches based on conditional independence tests are among the most popular methods for learning graphical models from data. Due to the predominance of Bayesian networks in th...
Christian Borgelt
CVIU
2008
192views more  CVIU 2008»
15 years 2 months ago
Content based video matching using spatiotemporal volumes
This paper presents a novel framework for matching video sequences using the spatiotemporal segmentation of videos. Instead of using appearance features for region correspondence ...
Arslan Basharat, Yun Zhai, Mubarak Shah
132
Voted
ICCV
2009
IEEE
15 years 10 months ago
Multiperspective Stereo Matching and Volumetric Reconstruction
Stereo matching and volumetric reconstruction are the most explored 3D scene recovery techniques in computer vision. Many existing approaches assume perspective input images and us...
Yuanyuan Ding, Jingyi Yu, and Peter Sturm
COLT
2001
Springer
15 years 7 months ago
Intrinsic Complexity of Learning Geometrical Concepts from Positive Data
Intrinsic complexity is used to measure the complexity of learning areas limited by broken-straight lines (called open semi-hulls) and intersections of such areas. Any strategy le...
Sanjay Jain, Efim B. Kinber