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ICML
2000
IEEE
16 years 7 months ago
Correlation-based Feature Selection for Discrete and Numeric Class Machine Learning
Algorithms for feature selection fall into two broad categories: wrappers that use the learning algorithm itself to evaluate the usefulness of features and filters that evaluate f...
Mark A. Hall
ROBOCUP
2004
Springer
97views Robotics» more  ROBOCUP 2004»
15 years 12 months ago
The UT Austin Villa 2003 Champion Simulator Coach: A Machine Learning Approach
The UT Austin Villa 2003 simulated online soccer coach was a first time entry in the RoboCup Coach Competition. In developing the coach, the main research focus was placed on trea...
Gregory Kuhlmann, Peter Stone, Justin Lallinger
ACL
1998
15 years 8 months ago
Trainable, Scalable Summarization Using Robust NLP and Machine Learning
We describe a trainable and scalable summarization system which utilizes features derived from information retrieval, information extraction, and NLP techniques and on-line resour...
Chinatsu Aone, Mary Ellen Okurowski, James Gorlins...
AAAI
1994
15 years 7 months ago
Inducing Deterministic Prolog Parsers from Treebanks: A Machine Learning Approach
or untagged treebanks. ' When trained on an untagged This paper presents a method for constructing deterministic Prolog parsers from corpora of parsed sentences. Our approach ...
John M. Zelle, Raymond J. Mooney
TCC
2005
Springer
102views Cryptology» more  TCC 2005»
16 years 13 hour ago
Handling Expected Polynomial-Time Strategies in Simulation-Based Security Proofs
The standard class of adversaries considered in cryptography is that of strict polynomial-time probabilistic machines. However, expected polynomial-time machines are often also co...
Jonathan Katz, Yehuda Lindell