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» Minimizing Learned Clauses
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SIGIR
2004
ACM
15 years 10 months ago
Focused named entity recognition using machine learning
In this paper we study the problem of finding most topical named entities among all entities in a document, which we refer to as focused named entity recognition. We show that th...
Li Zhang, Yue Pan, Tong Zhang
FORTE
2008
15 years 6 months ago
Detecting Communication Protocol Security Flaws by Formal Fuzz Testing and Machine Learning
Network-based fuzz testing has become an effective mechanism to ensure the security and reliability of communication protocol systems. However, fuzz testing is still conducted in a...
Guoqiang Shu, Yating Hsu, David Lee
TKDE
2010
168views more  TKDE 2010»
15 years 3 months ago
Completely Lazy Learning
—Local classifiers are sometimes called lazy learners because they do not train a classifier until presented with a test sample. However, such methods are generally not complet...
Eric K. Garcia, Sergey Feldman, Maya R. Gupta, San...
JMLR
2010
147views more  JMLR 2010»
14 years 11 months ago
Spectral Regularization Algorithms for Learning Large Incomplete Matrices
We use convex relaxation techniques to provide a sequence of regularized low-rank solutions for large-scale matrix completion problems. Using the nuclear norm as a regularizer, we...
Rahul Mazumder, Trevor Hastie, Robert Tibshirani
COLT
1999
Springer
15 years 9 months ago
Regret Bounds for Prediction Problems
We present a unified framework for reasoning about worst-case regret bounds for learning algorithms. This framework is based on the theory of duality of convex functions. It brin...
Geoffrey J. Gordon