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» Learning Finite-State Models for Machine Translation
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ICDCS
2007
IEEE
15 years 3 months ago
Testing Security Properties of Protocol Implementations - a Machine Learning Based Approach
Security and reliability of network protocol implementations are essential for communication services. Most of the approaches for verifying security and reliability, such as forma...
Guoqiang Shu, David Lee
COLING
2002
14 years 9 months ago
A Comparative Evaluation of Data-driven Models in Translation Selection of Machine Translation
We present a comparative evaluation of two data-driven models used in translation selection of English-Korean machine translation. Latent semantic analysis(LSA) and probabilistic ...
Yuseop Kim, Jeong Ho Chang, Byoung-Tak Zhang
SMC
2007
IEEE
125views Control Systems» more  SMC 2007»
15 years 3 months ago
A hierarchical strategy for learning of robot walking strategies in natural terrain environments
– In this paper, we present a hierarchical methodology that learns new walking gaits autonomously while operating in an uncharted environment, such as on the Mars planetary surfa...
Ayanna M. Howard, Lonnie T. Parker
FASE
2008
Springer
14 years 11 months ago
Regular Inference for State Machines Using Domains with Equality Tests
Abstract. Existing algorithms for regular inference (aka automata learning) allows to infer a finite state machine by observing the output that the machine produces in response to ...
Therese Berg, Bengt Jonsson, Harald Raffelt
APIN
2002
121views more  APIN 2002»
14 years 9 months ago
Applying Learning by Examples for Digital Design Automation
This paper describes a new learning by example mechanism and its application for digital circuit design automation. This mechanism uses finite state machines to represent the infer...
Ben Choi