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Inductive programming
Inductive programming (IP) is a special area of automatic programming, covering research from artificial intelligence and programming, which…
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Related topics
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39 relations
Abductive logic programming
Action language
Artificial general intelligence
Automatic programming
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Broader (3)
Artificial intelligence
Logic programming
Machine learning
Papers overview
Semantic Scholar uses AI to extract papers important to this topic.
2018
2018
General-purpose Declarative Inductive Programming with Domain-Specific Background Knowledge for Data Wrangling Automation
Lidia Contreras Ochando
,
C. Ferri
,
J. Hernández-Orallo
,
Fernando Martínez-Plumed
,
M. Ramírez-Quintana
,
Susumu Katayama
arXiv.org
2018
Corpus ID: 52844725
Given one or two examples, humans are good at understanding how to solve a problem independently of its domain, because they are…
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2016
2016
General-Purpose Inductive Programming for Data Wrangling Automation
Lidia Contreras-Ochando
,
Fernando Martínez-Plumed
,
C. Ferri
,
J. Hernández-Orallo
,
M. Ramírez-Quintana
2016
Corpus ID: 46000607
Data acquisition, integration, transformation, cleansing and other highly tedious tasks take a large proportion of data science…
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2015
2015
Exploring Owner-Managers Perspectives to Develop A Conceptual Learning Framework
L. Strachan
2015
Corpus ID: 152168288
This study explores the learning experiences of owner-managers of micro- enterprises. The literature suggests that owner-managers…
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Review
2015
Review
2015
Approaches and Applications of Inductive Programming (Dagstuhl Seminar 15442)
J. Hernández-Orallo
,
S. Muggleton
,
Ute Schmid
,
B. Zorn
Dagstuhl Reports
2015
Corpus ID: 39375052
This report documents the program and the outcomes of Dagstuhl Seminar 15442 "Approaches and Applications of Inductive…
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Review
2014
Review
2014
Approaches and Applications of Inductive Programming
Sumit Gulwani
,
E. Kitzelmann
,
Ute Schmid
2014
Corpus ID: 266492768
This report documents the program and the outcomes of Dagstuhl Seminar 13502 “Approaches and Applications of Inductive…
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2013
2013
On the definition of a general learning system with user-defined operators
Fernando Martínez-Plumed
,
C. Ferri
,
J. Hernández-Orallo
,
M. Ramírez-Quintana
arXiv.org
2013
Corpus ID: 14399132
In this paper, we push forward the idea of machine learning systems whose operators can be modified and fine-tuned for each…
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2012
2012
Learning with Configurable Operators and RL-Based Heuristics
Fernando Martínez-Plumed
,
C. Ferri
,
J. Hernández-Orallo
,
M. Ramírez-Quintana
NFMCP
2012
Corpus ID: 15434165
In this paper, we push forward the idea of machine learning systems for which the operators can be modified and finetuned for…
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Review
2012
Review
2012
Design of Active Loop Antenna for Multi-band Radio Reception .
J. Hussein
,
Karbala
2012
Corpus ID: 189801075
A simple design method of multiband active loop antenna for multiband reception is presented, the propose antenna work for LW and…
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2006
2006
Inductive Programming by Expectation Maximization Algorithm
Roger Hsiao
2006
Corpus ID: 13191988
This paper proposes an algorithm which can write programs automatically to solve problems. We model the sequence of instructions…
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1997
1997
Evaluation of a semi-automated theorem prover
H. Lowe
1997
Corpus ID: 18872656
So little evaluation has been carried out on user interfaces to theorem provers that even the question of what should be…
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