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ALT
2006
Springer
14 years 6 months ago
Learning Linearly Separable Languages
This paper presents a novel paradigm for learning languages that consists of mapping strings to an appropriate high-dimensional feature space and learning a separating hyperplane i...
Leonid Kontorovich, Corinna Cortes, Mehryar Mohri
ACL
2010
13 years 7 months ago
cdec: A Decoder, Alignment, and Learning Framework for Finite-State and Context-Free Translation Models
We present cdec, an open source framework for decoding, aligning with, and training a number of statistical machine translation models, including word-based models, phrase-based m...
Chris Dyer, Adam Lopez, Juri Ganitkevitch, Jonatha...
ASPLOS
2004
ACM
14 years 2 months ago
Devirtualizable virtual machines enabling general, single-node, online maintenance
Maintenance is the dominant source of downtime at high availability sites. Unfortunately, the dominant mechanism for reducing this downtime, cluster rolling upgrade, has two short...
David E. Lowell, Yasushi Saito, Eileen J. Samberg
PAMI
2010
276views more  PAMI 2010»
13 years 7 months ago
Local-Learning-Based Feature Selection for High-Dimensional Data Analysis
—This paper considers feature selection for data classification in the presence of a huge number of irrelevant features. We propose a new feature selection algorithm that addres...
Yijun Sun, Sinisa Todorovic, Steve Goodison
COLT
1993
Springer
14 years 1 months ago
Parameterized Learning Complexity
We describe three applications in computational learning theory of techniques and ideas recently introduced in the study of parameterized computational complexity. (1) Using param...
Rodney G. Downey, Patricia A. Evans, Michael R. Fe...