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EH
1999
IEEE
351views Hardware» more  EH 1999»
14 years 1 months ago
Evolvable Hardware or Learning Hardware? Induction of State Machines from Temporal Logic Constraints
Here we advocate an approach to learning hardware based on induction of finite state machines from temporal logic constraints. The method involves training on examples, constraint...
Marek A. Perkowski, Alan Mishchenko, Anatoli N. Ch...
TSMC
2011
210views more  TSMC 2011»
13 years 4 months ago
Fault Diagnosis in Discrete-Event Systems: Incomplete Models and Learning
— Most state-based approaches to fault diagnosis of discrete-event systems require a complete and accurate model of the system to be diagnosed. In this paper, we address the prob...
Raymond H. Kwong, David L. Yonge-Mallo
ICML
2005
IEEE
14 years 9 months ago
Hedged learning: regret-minimization with learning experts
In non-cooperative multi-agent situations, there cannot exist a globally optimal, yet opponent-independent learning algorithm. Regret-minimization over a set of strategies optimiz...
Yu-Han Chang, Leslie Pack Kaelbling
CIKM
2006
Springer
14 years 22 days ago
Coupling feature selection and machine learning methods for navigational query identification
It is important yet hard to identify navigational queries in Web search due to a lack of sufficient information in Web queries, which are typically very short. In this paper we st...
Yumao Lu, Fuchun Peng, Xin Li, Nawaaz Ahmed
BMCBI
2007
129views more  BMCBI 2007»
13 years 9 months ago
Exploring inconsistencies in genome-wide protein function annotations: a machine learning approach
Background: Incorrectly annotated sequence data are becoming more commonplace as databases increasingly rely on automated techniques for annotation. Hence, there is an urgent need...
Carson M. Andorf, Drena Dobbs, Vasant Honavar