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ICML
2004
IEEE
14 years 8 months ago
Support vector machine learning for interdependent and structured output spaces
Learning general functional dependencies is one of the main goals in machine learning. Recent progress in kernel-based methods has focused on designing flexible and powerful input...
Ioannis Tsochantaridis, Thomas Hofmann, Thorsten J...
GECCO
2005
Springer
175views Optimization» more  GECCO 2005»
14 years 28 days ago
Meta-grammar constant creation with grammatical evolution by grammatical evolution
This study examines the utility of meta-grammar constant generation on a series of benchmark problems. The performance of the meta-grammar approach is compared to a grammar which ...
Ian Dempsey, Michael O'Neill, Anthony Brabazon
CSL
2002
Springer
13 years 7 months ago
Weighted finite-state transducers in speech recognition
We survey the use of weighted finite-state transducers (WFSTs) in speech recognition. We show that WFSTs provide a common and natural representation for HMM models, context-depend...
Mehryar Mohri, Fernando Pereira, Michael Riley
CEC
2010
IEEE
13 years 8 months ago
Evolving natural language grammars without supervision
Unsupervised grammar induction is one of the most difficult works of language processing. Its goal is to extract a grammar representing the language structure using texts without a...
Lourdes Araujo, Jesus Santamaria
GG
2008
Springer
13 years 8 months ago
Adaptive Star Grammars for Graph Models
Abstract. Adaptive star grammars generalize well-known graph grammar formalisms based on hyperedge and node replacement while retaining, e.g., parseability and the commutativity an...
Frank Drewes, Berthold Hoffmann, Mark Minas