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» Extracting Web Data Using Instance-Based Learning
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ICML
2010
IEEE
15 years 3 months ago
Learning Fast Approximations of Sparse Coding
In Sparse Coding (SC), input vectors are reconstructed using a sparse linear combination of basis vectors. SC has become a popular method for extracting features from data. For a ...
Karol Gregor, Yann LeCun
153
Voted
LWA
2007
15 years 4 months ago
Know the Right People? Recommender Systems for Web 2.0
Web 2.0 applications like Flickr, YouTube, or Del.icio.us are increasingly popular online communities for creating, editing and sharing content. However, the rapid increase in siz...
Stefan Siersdorfer, Sergej Sizov, Paul Clough
135
Voted
WWW
2003
ACM
16 years 3 months ago
Efficient URL caching for world wide web crawling
Crawling the web is deceptively simple: the basic algorithm is (a) Fetch a page (b) Parse it to extract all linked URLs (c) For all the URLs not seen before, repeat (a)?(c). Howev...
Andrei Z. Broder, Marc Najork, Janet L. Wiener
131
Voted
AAAI
2008
15 years 4 months ago
A Fast Data Collection and Augmentation Procedure for Object Recognition
When building an application that requires object class recognition, having enough data to learn from is critical for good performance, and can easily determine the success or fai...
Benjamin Sapp, Ashutosh Saxena, Andrew Y. Ng
97
Voted
ICML
2007
IEEE
16 years 3 months ago
Linear and nonlinear generative probabilistic class models for shape contours
We introduce a robust probabilistic approach to modeling shape contours based on a lowdimensional, nonlinear latent variable model. In contrast to existing techniques that use obj...
Graham McNeill, Sethu Vijayakumar