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NLPRS
2001
Springer
15 years 10 months ago
Learning Strategies In A Grammar Induction Framework
This work extends a semi-automatic grammar induction approach previously proposed in [1]. We investigate the use of Information Gain (IG) in place of Mutual Information (MI) for g...
Chin-Chung Wong, Helen M. Meng, Kai-Chung Siu
IJAIT
2002
81views more  IJAIT 2002»
15 years 6 months ago
Guiding Constructive Search with Statistical Instance-Based Learning
Several real world applications involve solving combinatorial optimization problems. Commonly, existing heuristic approaches are designed to address specific difficulties of the u...
Orestis Telelis, Panagiotis Stamatopoulos
BMCBI
2007
91views more  BMCBI 2007»
15 years 6 months ago
A machine learning approach for the identification of odorant binding proteins from sequence-derived properties
Background: Odorant binding proteins (OBPs) are believed to shuttle odorants from the environment to the underlying odorant receptors, for which they could potentially serve as od...
Ganesan Pugalenthi, E. Ke Tang, Ponnuthurai N. Sug...
TON
2010
167views more  TON 2010»
15 years 1 months ago
A Machine Learning Approach to TCP Throughput Prediction
TCP throughput prediction is an important capability in wide area overlay and multi-homed networks where multiple paths may exist between data sources and receivers. In this paper...
Mariyam Mirza, Joel Sommers, Paul Barford, Xiaojin...
JMLR
2012
13 years 8 months ago
Contextual Bandit Learning with Predictable Rewards
Contextual bandit learning is a reinforcement learning problem where the learner repeatedly receives a set of features (context), takes an action and receives a reward based on th...
Alekh Agarwal, Miroslav Dudík, Satyen Kale,...