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» The complexity of learning SUBSEQ(A)
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ICML
2004
IEEE
16 years 7 months ago
Semi-supervised learning using randomized mincuts
In many application domains there is a large amount of unlabeled data but only a very limited amount of labeled training data. One general approach that has been explored for util...
Avrim Blum, John D. Lafferty, Mugizi Robert Rweban...
VLDB
2003
ACM
165views Database» more  VLDB 2003»
16 years 6 months ago
Learning to match ontologies on the Semantic Web
On the Semantic Web, data will inevitably come from many different ontologies, and information processing across ontologies is not possible without knowing the semantic mappings be...
AnHai Doan, Jayant Madhavan, Robin Dhamankar, Pedr...
ICCV
2007
IEEE
16 years 1 months ago
Fast Automatic Heart Chamber Segmentation from 3D CT Data Using Marginal Space Learning and Steerable Features
Multi-chamber heart segmentation is a prerequisite for global quantification of the cardiac function. The complexity of cardiac anatomy, poor contrast, noise or motion artifacts ...
Yefeng Zheng, Adrian Barbu, Bogdan Georgescu, Mich...
IROS
2006
IEEE
127views Robotics» more  IROS 2006»
16 years 21 days ago
Learning Predictive Features in Affordance based Robotic Perception Systems
This work is about the relevance of Gibson’s concept of affordances [1] for visual perception in interactive and autonomous robotic systems. In extension to existing functional ...
Gerald Fritz, Lucas Paletta, Ralph Breithaupt, Eri...
STOC
2000
ACM
174views Algorithms» more  STOC 2000»
15 years 11 months ago
Noise-tolerant learning, the parity problem, and the statistical query model
We describe a slightly subexponential time algorithm for learning parity functions in the presence of random classification noise, a problem closely related to several cryptograph...
Avrim Blum, Adam Kalai, Hal Wasserman