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Özgür Akgün
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2020 – today
- 2024
- [j9]Xu Zhu
, Miguel A. Nacenta, Özgür Akgün
Solvi: A visual constraint modeling tool. J. Comput. Lang. 78: 101242 (2024) - [c27]Erdem Kus, Özgür Akgün, Nguyen Dang, Ian Miguel:
Frugal Algorithm Selection (Short Paper). CP 2024: 38:1-38:16 - [i19]Erdem Kus, Özgür Akgün, Nguyen Dang, Ian Miguel:
Frugal Algorithm Selection. CoRR abs/2405.11059 (2024) - [i18]Alessio Pellegrino, Özgür Akgün, Nguyen Dang, Zeynep Kiziltan, Ian Miguel:
Automatic Feature Learning for Essence: a Case Study on Car Sequencing. CoRR abs/2409.15158 (2024) - 2023
- [j8]Patrick Spracklen, Nguyen Dang
Automated streamliner portfolios for constraint satisfaction problems. Artif. Intell. 319: 103915 (2023) - [c26]Carlo Cena
Learning When to Use Automatic Tabulation in Constraint Model Reformulation. IJCAI 2023: 1902-1910 - [c25]Özgür Akgün
Conjure: Automatic Generation of Constraint Models from Problem Specifications (Extended Abstract). IJCAI 2023: 6833-6838 - [c24]Alan Dearle, Graham N. C. Kirby, Özgür Akgün:
An Approach to Population Linkage using Graph Databases. SEBD 2023: 291-302 - [i17]Ruth Hoffmann, Özgür Akgün, Christopher Jefferson:
Composable Constraint Models for Permutation Enumeration. CoRR abs/2311.17581 (2023) - 2022
- [j7]Özgür Akgün
Conjure: Automatic Generation of Constraint Models from Problem Specifications. Artif. Intell. 310: 103751 (2022) - [j6]Özgür Akgün
Enumeration of set-theoretic solutions to the Yang-Baxter equation. Math. Comput. 91(335): 1469-1481 (2022) - [c23]Nguyen Dang
A Framework for Generating Informative Benchmark Instances. CP 2022: 18:1-18:18 - [c22]Ruth Hoffmann
Understanding How People Approach Constraint Modelling and Solving. CP 2022: 28:1-28:18 - [i16]Özgür Akgün
Automatic Tabulation in Constraint Models. CoRR abs/2202.13250 (2022) - [i15]Nguyen Dang, Özgür Akgün, Joan Espasa
A Framework for Generating Informative Benchmark Instances. CoRR abs/2205.14753 (2022) - 2021
- [c21]Özgür Akgün
Finding Subgraphs with Side Constraints. CPAIOR 2021: 348-364 - [i14]Özgür Akgün
Towards Reformulating Essence Specifications for Robustness. CoRR abs/2111.00821 (2021) - 2020
- [j5]Xu Zhu
How People Visually Represent Discrete Constraint Problems. IEEE Trans. Vis. Comput. Graph. 26(8): 2603-2619 (2020) - [c20]Ewan Davidson, Özgür Akgün
Effective Encodings of Constraint Programming Models to SMT. CP 2020: 143-159 - [c19]Özgür Akgün
Discriminating Instance Generation from Abstract Specifications: A Case Study with CP and MIP. CPAIOR 2020: 41-51 - [c18]Gökberk Koçak
Exploiting Incomparability in Solution Dominance: Improving General Purpose Constraint-Based Mining. ECAI 2020: 331-338 - [i13]Patrick Spracklen, Nguyen Dang
Towards Portfolios of Streamlined Constraint Models: A Case Study with the Balanced Academic Curriculum Problem. CoRR abs/2009.10152 (2020) - [i12]Özgür Akgün
Exploring Instance Generation for Automated Planning. CoRR abs/2009.10156 (2020) - [i11]Gökberk Koçak, Özgür Akgün
Efficient Incremental Modelling and Solving. CoRR abs/2009.11111 (2020)
2010 – 2019
- 2019
- [j4]Özgür Akgün, Ian P. Gent, Sergey Kitaev, Hans Zantema:
Solving Computational Problems in the Theory of Word-Representable Graphs. J. Integer Seq. 22(2): 19.2.5 (2019) - [j3]Blesson Varghese
Cloud Benchmarking for Maximising Performance of Scientific Applications. IEEE Trans. Cloud Comput. 7(1): 170-182 (2019) - [c17]Özgür Akgün
Instance Generation via Generator Instances. CP 2019: 3-19 - [c16]Patrick Spracklen, Nguyen Dang
Automatic Streamlining for Constrained Optimisation. CP 2019: 366-383 - [i10]Özgür Akgün, András Z. Salamon:
Conjure Documentation, Release 2.3.0. CoRR abs/1910.00475 (2019) - [i9]Gökberk Koçak, Özgür Akgün, Tias Guns, Ian Miguel:
Towards Improving Solution Dominance with Incomparability Conditions: A case-study using Generator Itemset Mining. CoRR abs/1910.00505 (2019) - 2018
- [c15]Özgür Akgün
Automatic Discovery and Exploitation of Promising Subproblems for Tabulation. CP 2018: 3-12 - [c14]Patrick Spracklen, Özgür Akgün
Automatic Generation and Selection of Streamlined Constraint Models via Monte Carlo Search on a Model Lattice. CP 2018: 362-372 - [c13]Özgür Akgün
Metamorphic Testing of Constraint Solvers. CP 2018: 727-736 - [c12]Gokberk Kocak
Closed Frequent Itemset Mining with Arbitrary Side Constraints. ICDM Workshops 2018: 1224-1232 - [c11]Özgür Akgün
A Framework for Constraint Based Local Search using Essence. IJCAI 2018: 1242-1248 - [c10]Özgür Akgün
Using Metric Space Indexing for Complete and Efficient Record Linkage. PAKDD (3) 2018: 89-101 - [i8]Özgür Akgün
Modelling Langford's Problem: A Viewpoint for Search. CoRR abs/1808.09847 (2018) - [i7]Ruth Hoffmann
Memory Consistency Models using Constraints. CoRR abs/1808.09870 (2018) - 2017
- [j2]Peter Nightingale
Automatically improving constraint models in Savile Row. Artif. Intell. 251: 35-61 (2017) - [j1]Özgür Akgün
Extensible automated constraint modelling via refinement of abstract problem specifications. Constraints An Int. J. 22(1): 91-92 (2017) - [i6]Roberto Rossi, Özgür Akgün, Steven D. Prestwich, S. Armagan Tarim:
Declarative Statistics. CoRR abs/1708.01829 (2017) - 2016
- [c9]Özgür Akgün
Exploiting Short Supports for Improved Encoding of Arbitrary Constraints into SAT. CP 2016: 3-12 - [i5]Blesson Varghese, Ozgur Akgun, Ian Miguel, Long Thai, Adam Barker:
Cloud Benchmarking For Maximising Performance of Scientific Applications. CoRR abs/1608.00406 (2016) - [i4]Roberto Rossi, Özgür Akgün, Steven D. Prestwich, Armagan Tarim:
The BIN_COUNTS Constraint: Filtering and Applications. CoRR abs/1611.08942 (2016) - 2015
- [c8]James Wetter, Özgür Akgün
Automatically Generating Streamlined Constraint Models with Essence and Conjure. CP 2015: 480-496 - [c7]James Wetter, Ozgur Akgun
Cloud-based E-Infrastructure for Scheduling Astronomical Observations. e-Science 2015: 362-370 - 2014
- [b1]Özgür Akgün:
Extensible automated constraint modelling via refinement of abstract problem specifications. University of St Andrews, UK, 2014 - [c6]Blesson Varghese, Ozgur Akgun
Cloud Benchmarking for Performance. CloudCom 2014: 535-540 - [c5]Long Thai, Adam Barker, Blesson Varghese, Ozgur Akgun
Optimal Deployment of Geographically Distributed Workflow Engines on the Cloud. CloudCom 2014: 811-816 - [c4]Peter Nightingale
Automatically Improving Constraint Models in Savile Row through Associative-Commutative Common Subexpression Elimination. CP 2014: 590-605 - [c3]Ozgur Akgun
Breaking Conditional Symmetry in Automated Constraint Modelling with CONJURE. ECAI 2014: 3-8 - [i3]Long Thai, Adam Barker, Blesson Varghese, Ozgur Akgun
Optimal Deployment of Geographically Distributed Workflow Engines on the Cloud. CoRR abs/1410.8359 (2014) - [i2]Blesson Varghese, Ozgur Akgun
Cloud Benchmarking for Performance. CoRR abs/1411.0912 (2014) - 2013
- [c2]Ozgur Akgun
Automated Symmetry Breaking and Model Selection in Conjure. CP 2013: 107-116 - 2011
- [c1]Ozgur Akgun, Ian Miguel, Christopher Jefferson, Alan M. Frisch, Brahim Hnich:
Extensible Automated Constraint Modelling. AAAI 2011: 4-11 - [i1]Ozgur Akgun, Alan M. Frisch, Brahim Hnich, Christopher Jefferson, Ian Miguel:
Conjure Revisited: Towards Automated Constraint Modelling. CoRR abs/1109.1774 (2011)
Coauthor Index
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last updated on 2024-10-16 20:32 CEST by the dblp team
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