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» Learning a Classification Model for Segmentation
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ICML
2006
IEEE
16 years 5 months ago
Nightmare at test time: robust learning by feature deletion
When constructing a classifier from labeled data, it is important not to assign too much weight to any single input feature, in order to increase the robustness of the classifier....
Amir Globerson, Sam T. Roweis
130
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IWANN
2005
Springer
15 years 10 months ago
Co-evolutionary Learning in Liquid Architectures
A large class of problems requires real-time processing of complex temporal inputs in real-time. These are difficult tasks for state-of-the-art techniques, since they require captu...
Igal Raichelgauz, Karina Odinaev, Yehoshua Y. Zeev...
IJCAI
2007
15 years 6 months ago
Incremental Learning of Perceptual Categories for Open-Domain Sketch Recognition
Most existing sketch understanding systems require a closed domain to achieve recognition. This paper describes an incremental learning technique for opendomain recognition. Our s...
Andrew M. Lovett, Morteza Dehghani, Kenneth D. For...
ACL
2009
15 years 2 months ago
Semi-supervised Learning for Automatic Prosodic Event Detection Using Co-training Algorithm
Most of previous approaches to automatic prosodic event detection are based on supervised learning, relying on the availability of a corpus that is annotated with the prosodic lab...
Je Hun Jeon, Yang Liu
ICCV
2007
IEEE
16 years 6 months ago
Supervised Learning of Image Restoration with Convolutional Networks
Convolutional networks have achieved a great deal of success in high-level vision problems such as object recognition. Here we show that they can also be used as a general method ...
Viren Jain, Joseph F. Murray, Fabian Roth, Sriniva...