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HPDC
2010
IEEE
15 years 7 months ago
ParaText: scalable text modeling and analysis
Automated analysis of unstructured text documents (e.g., web pages, newswire articles, research publications, business reports) is a key capability for solving important problems ...
Daniel M. Dunlavy, Timothy M. Shead, Eric T. Stant...
ACL
2009
15 years 4 months ago
Stochastic Gradient Descent Training for L1-regularized Log-linear Models with Cumulative Penalty
Stochastic gradient descent (SGD) uses approximate gradients estimated from subsets of the training data and updates the parameters in an online fashion. This learning framework i...
Yoshimasa Tsuruoka, Jun-ichi Tsujii, Sophia Anania...
COMSUR
2011
203views Hardware» more  COMSUR 2011»
14 years 6 months ago
Overcoming Adversaries in Sensor Networks: A Survey of Theoretical Models and Algorithmic Approaches for Tolerating Malicious In
Interference is an unavoidable property of the wireless communication medium and, in sensor networks, such interference is exacerbated due to the energy-starved nature of the netw...
Maxwell Young, Raouf Boutaba
WWW
2009
ACM
16 years 7 months ago
Web 2.0: blind to an accessible new world
With the advent of Web 2.0 technologies, websites have evolved from static pages to dynamic, interactive Web-based applications with the ability to replicate common desktop functi...
Joshua M. Hailpern, Loretta Guarino Reid, Richard ...
ICCV
2005
IEEE
16 years 8 months ago
Probabilistic Boosting-Tree: Learning Discriminative Models for Classification, Recognition, and Clustering
In this paper, a new learning framework?probabilistic boosting-tree (PBT), is proposed for learning two-class and multi-class discriminative models. In the learning stage, the pro...
Zhuowen Tu