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» MABLE: a framework for learning from natural instruction
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TSMC
2008
100views more  TSMC 2008»
14 years 9 months ago
Instruction-Matrix-Based Genetic Programming
In genetic programming (GP), evolving tree nodes separately would reduce the huge solution space. However, tree nodes are highly interdependent with respect to their fitness. In th...
Gang Li, Jin Feng Wang, Kin-Hong Lee, Kwong-Sak Le...
80
Voted
CADE
2008
Springer
15 years 10 months ago
Combining Theorem Proving with Natural Language Processing
Abstract. The LogAnswer system is an application of automated reasoning to the field of open domain question-answering, the retrieval of answers to natural language questions regar...
Björn Pelzer, Ingo Glöckner
ICGI
1998
Springer
15 years 1 months ago
Learning Stochastic Finite Automata from Experts
We present in this paper a new learning problem called learning distributions from experts. In the case we study the experts are stochastic deterministic finite automata (sdfa). W...
Colin de la Higuera
IJCAI
2007
14 years 11 months ago
Learning from Partial Observations
We present a general machine learning framework for modelling the phenomenon of missing information in data. We propose a masking process model to capture the stochastic nature of...
Loizos Michael
EH
1999
IEEE
351views Hardware» more  EH 1999»
15 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...