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» Learning on the Test Data: Leveraging Unseen Features
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SIGMOD
2012
ACM
232views Database» more  SIGMOD 2012»
11 years 11 months ago
Large-scale machine learning at twitter
The success of data-driven solutions to difficult problems, along with the dropping costs of storing and processing massive amounts of data, has led to growing interest in largesc...
Jimmy Lin, Alek Kolcz
ACCV
2010
Springer
13 years 4 months ago
Face Recognition with Decision Tree-Based Local Binary Patterns
Many state-of-the-art face recognition algorithms use image descriptors based on features known as Local Binary Patterns (LBPs). While many variations of LBP exist, so far none of ...
Daniel Maturana, Domingo Mery, Alvaro Soto
AIPRF
2007
13 years 10 months ago
Evaluation of Different Approaches to Training a Genre Classifier
This paper presents experiments on classifying web pages by genre. Firstly, a corpus of 1539 manually labeled web pages was prepared. Secondly, 502 genre features were selected ba...
Vedrana Vidulin, Mitja Lustrek, Matjaz Gams
JMLR
2010
152views more  JMLR 2010»
13 years 3 months ago
The SHOGUN Machine Learning Toolbox
We have developed a machine learning toolbox, called SHOGUN, which is designed for unified large-scale learning for a broad range of feature types and learning settings. It offers...
Sören Sonnenburg, Gunnar Rätsch, Sebasti...
SIGCSE
2008
ACM
153views Education» more  SIGCSE 2008»
13 years 7 months ago
A cross-domain visual learning engine for interactive generation of instructional materials
We present the design and development of a Visual Learning Engine, a tool that can form the basis for interactive development of visually rich teaching and learning modules across...
K. R. Subramanian, T. Cassen