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AI
2011
Springer
14 years 5 months ago
Learning qualitative models from numerical data
Qualitative models are often a useful abstraction of the physical world. Learning qualitative models from numerical data sible way to obtain such an abstraction. We present a new ...
Jure Zabkar, Martin Mozina, Ivan Bratko, Janez Dem...
ICCV
2011
IEEE
13 years 10 months ago
Perturb-and-MAP Random Fields: Using Discrete Optimization\\to Learn and Sample from Energy Models
We propose a novel way to induce a random field from an energy function on discrete labels. It amounts to locally injecting noise to the energy potentials, followed by finding t...
George Papandreou, Alan L. Yuille
IROS
2009
IEEE
198views Robotics» more  IROS 2009»
15 years 5 months ago
Scalable learning for object detection with GPU hardware
Abstract— We consider the problem of robotic object detection of such objects as mugs, cups, and staplers in indoor environments. While object detection has made significant pro...
Adam Coates, Paul Baumstarck, Quoc V. Le, Andrew Y...
ICPP
2007
IEEE
15 years 5 months ago
A Meta-Learning Failure Predictor for Blue Gene/L Systems
The demand for more computational power in science and engineering has spurred the design and deployment of ever-growing cluster systems. Even though the individual components use...
Prashasta Gujrati, Yawei Li, Zhiling Lan, Rajeev T...
ACSAC
2005
IEEE
15 years 4 months ago
Lessons Learned: A Security Analysis of the Internet Chess Club
The Internet Chess Club (ICC) is a popular online chess server with more than 30,000 members worldwide including various celebrities and the best chess players in the world. Altho...
John Black, Martin Cochran, Martin Ryan Gardner