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» On Optimal Learning Algorithms for Multiplicity Automata
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CORR
2010
Springer
128views Education» more  CORR 2010»
13 years 8 months ago
Sublinear Optimization for Machine Learning
Abstract--We give sublinear-time approximation algorithms for some optimization problems arising in machine learning, such as training linear classifiers and finding minimum enclos...
Kenneth L. Clarkson, Elad Hazan, David P. Woodruff
NABIC
2010
13 years 3 months ago
Evolutionary design of edge detector using rule-changing Cellular automata
A new design method for Cellular automata (CA) rules are described. We have already proposed a method for designing the transition rules of two-dimensional 256-state CA for graysca...
Shohei Sato, Hitoshi Kanoh
COLT
2006
Springer
14 years 7 days ago
Learning Rational Stochastic Languages
Given a finite set of words w1, . . . , wn independently drawn according to a fixed unknown distribution law P called a stochastic language, an usual goal in Grammatical Inference ...
François Denis, Yann Esposito, Amaury Habra...
EMNLP
2011
12 years 8 months ago
Training dependency parsers by jointly optimizing multiple objectives
We present an online learning algorithm for training parsers which allows for the inclusion of multiple objective functions. The primary example is the extension of a standard sup...
Keith Hall, Ryan T. McDonald, Jason Katz-Brown, Mi...
GLOBECOM
2007
IEEE
14 years 2 months ago
Stochastic Channel Selection in Cognitive Radio Networks
— In this paper, we investigate the channel selection strategy for secondary users in cognitive radio networks. We claim that in order to avoid the costly channel switchings, a s...
Yang Song, Yuguang Fang, Yanchao Zhang