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KDD
2009
ACM
172views Data Mining» more  KDD 2009»
14 years 2 months ago
Learning dynamic temporal graphs for oil-production equipment monitoring system
Learning temporal graph structures from time series data reveals important dependency relationships between current observations and histories. Most previous work focuses on learn...
Yan Liu, Jayant R. Kalagnanam, Oivind Johnsen
ECCV
2006
Springer
14 years 11 months ago
Learning to Combine Bottom-Up and Top-Down Segmentation
Bottom-up segmentation based only on low-level cues is a notoriously difficult problem. This difficulty has lead to recent top-down segmentation algorithms that are based on class-...
Anat Levin, Yair Weiss
WWW
2006
ACM
14 years 10 months ago
Browsing on small screens: recasting web-page segmentation into an efficient machine learning framework
Fitting enough information from webpages to make browsing on small screens compelling is a challenging task. One approach is to present the user with a thumbnail image of the full...
Shumeet Baluja
HYBRID
1998
Springer
14 years 2 months ago
High Order Eigentensors as Symbolic Rules in Competitive Learning
We discuss properties of high order neurons in competitive learning. In such neurons, geometric shapes replace the role of classic `point' neurons in neural networks. Complex ...
Hod Lipson, Hava T. Siegelmann
CVPR
2011
IEEE
13 years 6 months ago
Learning Message-Passing Inference Machines for Structured Prediction
Nearly every structured prediction problem in computer vision requires approximate inference due to large and complex dependencies among output labels. While graphical models prov...
Stephane Ross, Daniel Munoz, J. Andrew Bagnell