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» Learning recursive functions: A survey
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145
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EUROGP
2010
Springer
166views Optimization» more  EUROGP 2010»
15 years 9 months ago
Learning a Lot from Only a Little: Genetic Programming for Panel Segmentation on Sparse Sensory Evaluation Data
We describe a data mining framework that derives panelist information from sparse flavour survey data. One component of the framework executes genetic programming ensemble based s...
Katya Vladislavleva, Kalyan Veeramachaneni, Una-Ma...
ESOP
2008
Springer
15 years 6 months ago
Verification of Higher-Order Computation: A Game-Semantic Approach
Abstract. We survey recent developments in an approach to the verification of higher-order computation based on game semantics. Higherorder recursion schemes are in essence (progra...
C.-H. Luke Ong
ICASSP
2011
IEEE
14 years 8 months ago
A sliding-window online fast variational sparse Bayesian learning algorithm
In this work a new online learning algorithm that uses automatic relevance determination (ARD) is proposed for fast adaptive nonlinear filtering. A sequential decision rule for i...
Thomas Buchgraber, Dmitriy Shutin, H. Vincent Poor
131
Voted
FSTTCS
2007
Springer
15 years 10 months ago
Program Analysis Using Weighted Pushdown Systems
Abstract. Pushdown systems (PDSs) are an automata-theoretic formalism for specifying a class of infinite-state transition systems. Infiniteness comes from the fact that each con...
Thomas W. Reps, Akash Lal, Nicholas Kidd
138
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ESANN
2004
15 years 5 months ago
Neural methods for non-standard data
Standard pattern recognition provides effective and noise-tolerant tools for machine learning tasks; however, most approaches only deal with real vectors of a finite and fixed dime...
Barbara Hammer, Brijnesh J. Jain