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» The Tradeoffs of Large Scale Learning
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ICML
2003
IEEE
14 years 8 months ago
Exploration and Exploitation in Adaptive Filtering Based on Bayesian Active Learning
In the task of adaptive information filtering, a system receives a stream of documents but delivers only those that match a person's information need. As the system filters i...
Yi Zhang, Wei Xu, James P. Callan
ACL
2008
13 years 9 months ago
Semi-Supervised Sequential Labeling and Segmentation Using Giga-Word Scale Unlabeled Data
This paper provides evidence that the use of more unlabeled data in semi-supervised learning can improve the performance of Natural Language Processing (NLP) tasks, such as part-o...
Jun Suzuki, Hideki Isozaki
CIDR
2009
157views Algorithms» more  CIDR 2009»
13 years 9 months ago
SCADS: Scale-Independent Storage for Social Computing Applications
Collaborative web applications such as Facebook, Flickr and Yelp present new challenges for storing and querying large amounts of data. As users and developers are focused more on...
Michael Armbrust, Armando Fox, David A. Patterson,...
MICCAI
2010
Springer
13 years 6 months ago
Automated Macular Pathology Diagnosis in Retinal OCT Images Using Multi-Scale Spatial Pyramid with Local Binary Patterns
We address a novel problem domain in the analysis of optical coherence tomography (OCT) images: the diagnosis of multiple macular pathologies in retinal OCT images. The goal is to ...
Yu-Ying Liu, Mei Chen, Hiroshi Ishikawa 0002, Gadi...
IFIP12
2008
13 years 9 months ago
P-Prism: A Computationally Efficient Approach to Scaling up Classification Rule Induction
Top Down Induction of Decision Trees (TDIDT) is the most commonly used method of constructing a model from a dataset in the form of classification rules to classify previously unse...
Frederic T. Stahl, Max A. Bramer, Mo Adda