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GECCO
2010
Springer
173views Optimization» more  GECCO 2010»
13 years 8 months ago
Superstate identification for state machines using search-based clustering
State machines are a popular method of representing a syshigh level of abstraction that enables developers to gain an overview of the system they represent and quickly understand ...
Mathew Hall, Phil McMinn, Neil Walkinshaw
JAR
2006
103views more  JAR 2006»
13 years 8 months ago
A Framework for Verifying Bit-Level Pipelined Machines Based on Automated Deduction and Decision Procedures
We describe an approach to verifying bit-level pipelined machine models using a combination of deductive reasoning and decision procedures. While theorem proving systems such as AC...
Panagiotis Manolios, Sudarshan K. Srinivasan
FINTAL
2006
13 years 11 months ago
Paraphrase Identification on the Basis of Supervised Machine Learning Techniques
Abstract. This paper presents a machine learning approach for paraphrase identification which uses lexical and semantic similarity information. In the experimental studies, we exam...
Zornitsa Kozareva, Andrés Montoyo
CIT
2004
Springer
13 years 11 months ago
BioPubMiner: Machine Learning Component-Based Biomedical Information Analysis Platform
Abstract. In this paper we introduce BioPubMiner, a machine learning component-based platform for biomedical information analysis. BioPubMiner employs natural language processing t...
Jae-Hong Eom, Byoung-Tak Zhang
TVLSI
2008
124views more  TVLSI 2008»
13 years 7 months ago
A Refinement-Based Compositional Reasoning Framework for Pipelined Machine Verification
Abstract--We present a refinement-based compositional framework for showing that pipelined machines satisfy the same safety and liveness properties as their non-pipelined specifica...
Panagiotis Manolios, Sudarshan K. Srinivasan