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A total of 66 records were found in 0.266 seconds
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A Regression-Based Methodology for Online Algorithm Selection
Hans Degroote, Patrick De Causmaecker, Bernd Bischl, Lars Kotthoff
SOCS, 37-45, 2018
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Containerisation and Dynamic Frameworks in ICCMA'19
Stefano Bistarelli, Lars Kotthoff, Francesco Santini 0001, Carlo Taticchi
SAFA@COMMA, 4-9, 2018
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Quantifying Algorithmic Improvements over Time
Lars Kotthoff, Alexandre Fréchette, Tomasz P. Michalak, Talal Rahwan, Holger H. Hoos, Kevin Leyton-Brown
IJCAI, 5165-5171, 2018
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The ICON Challenge on Algorithm Selection
Lars Kotthoff, Barry Hurley 0001, Barry O'Sullivan
AI Magazine, 38(2):91-93, 2017
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Auto-WEKA 2.0: Automatic model selection and hyperparameter optimization in WEKA
Lars Kotthoff, Chris Thornton, Holger H. Hoos, Frank Hutter, Kevin Leyton-Brown
Journal of Machine Learning Research, 1825:1-25:5, 2017
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mlr: Machine Learning in R
Bernd Bischl, Michel Lang, Lars Kotthoff, Julia Schiffner, Jakob Richter, Erich Studerus, Giuseppe Casalicchio, Zachary M. Jones
Journal of Machine Learning Research, 17170:1-170:5, 2016
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Proceedings of the 2016 Workshop on Automatic Machine Learning, AutoML 2016, co-located with 33rd International Conference on Machine Learning (ICML 2016), New York City, NY, USA, June 24, 2016
Frank Hutter, Lars Kotthoff, Joaquin Vanschoren
64, 2016
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ASlib: A benchmark library for algorithm selection
Bernd Bischl, Pascal Kerschke, Lars Kotthoff, Marius Thomas Lindauer, Yuri Malitsky, Alexandre Fréchette, Holger H. Hoos, Frank Hutter, Kevin Leyton-Brown, Kevin Tierney, Joaquin Vanschoren
Artif. Intell., 23741-58, 2016
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Using the Shapley Value to Analyze Algorithm Portfolios
Alexandre Fréchette, Lars Kotthoff, Tomasz P. Michalak, Talal Rahwan, Holger H. Hoos, Kevin Leyton-Brown
AAAI, 3397-3403, 2016
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mlr Tutorial
Julia Schiffner, Bernd Bischl, Michel Lang, Jakob Richter, Zachary M. Jones, Philipp Probst, Florian Pfisterer, Mason Gallo, Dominik Kirchhoff, Tobias Kühn, Janek Thomas, Lars Kotthoff
CoRR, abs/1609.06146, 2016
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Reinforcement Learning for Automatic Online Algorithm Selection - an Empirical Study
Hans Degroote, Bernd Bischl, Lars Kotthoff, Patrick De Causmaecker
ITAT, 93-101, 2016
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Data Mining and Constraint Programming - Foundations of a Cross-Disciplinary Approach
Christian Bessiere, Luc De Raedt, Lars Kotthoff, Siegfried Nijssen, Barry O'Sullivan, Dino Pedreschi
Springer,, Lecture Notes in Computer Science, ISBN: 978-3-319-50136-910101, 2016
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The Inductive Constraint Programming Loop
Christian Bessiere, Luc De Raedt, Tias Guns, Lars Kotthoff, Mirco Nanni, Siegfried Nijssen, Barry O'Sullivan, Anastasia Paparrizou, Dino Pedreschi, Helmut Simonis
Data Mining and Constraint Programming, 303-309, 2016
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ICON Loop Health Show Case
Barry Hurley 0001, Lars Kotthoff, Barry O'Sullivan, Helmut Simonis
Data Mining and Constraint Programming, 325-333, 2016
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Algorithm Selection for Combinatorial Search Problems: A Survey
Lars Kotthoff
Data Mining and Constraint Programming, 149-190, 2016
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ICON Loop Carpooling Show Case
Mirco Nanni, Lars Kotthoff, Riccardo Guidotti, Barry O'Sullivan, Dino Pedreschi
Data Mining and Constraint Programming, 310-324, 2016
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Advanced Portfolio Techniques
Barry Hurley 0001, Lars Kotthoff, Yuri Malitsky, Deepak Mehta, Barry O'Sullivan
Data Mining and Constraint Programming, 191-225, 2016
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Portfolios of Subgraph Isomorphism Algorithms
Lars Kotthoff, Ciaran McCreesh, Christine Solnon
LION, 107-122, 2016
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On Algorithm Selection, with an application to combinatorial search problems
Lars Kotthoff
Constraints, 20(4):481-482, 2015
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ASlib: A Benchmark Library for Algorithm Selection
Bernd Bischl, Pascal Kerschke, Lars Kotthoff, Marius Thomas Lindauer, Yuri Malitsky, Alexandre Fréchette, Holger H. Hoos, Frank Hutter, Kevin Leyton-Brown, Kevin Tierney, Joaquin Vanschoren
CoRR, abs/1506.02465, 2015
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ICON Challenge on Algorithm Selection
Lars Kotthoff
CoRR, abs/1511.04326, 2015
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The Inductive Constraint Programming Loop
Christian Bessiere, Luc De Raedt, Tias Guns, Lars Kotthoff, Mirco Nanni, Siegfried Nijssen, Barry O'Sullivan, Anastasia Paparrizou, Dino Pedreschi, Helmut Simonis
CoRR, abs/1510.03317, 2015
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Improving the State of the Art in Inexact TSP Solving Using Per-Instance Algorithm Selection
Lars Kotthoff, Pascal Kerschke, Holger Hoos, Heike Trautmann
LION, 202-217, 2015
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Find Your Way Back: Mobility Profile Mining with Constraints
Lars Kotthoff, Mirco Nanni, Riccardo Guidotti, Barry O'Sullivan
CP, 638-653, 2015
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Proceedings of the 2015 International Workshop on Meta-Learning and Algorithm Selection co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases 2015 (ECMLPKDD 2015), Porto, Portugal, September 7th, 2015
Joaquin Vanschoren, Pavel Brazdil, Christophe G. Giraud-Carrier, Lars Kotthoff
1455, 2015
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Top Tips to Make Your Research Irreproducible
Neil P. Chue Hong, Tom Crick, Ian P. Gent, Lars Kotthoff, Kenji Takeda
CoRR, abs/1504.00062, 2015
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Proceedings of the International Workshop on Meta-learning and Algorithm Selection co-located with 21st European Conference on Artificial Intelligence, MetaSel@ECAI 2014, Prague, Czech Republic, August 19, 2014
Joaquin Vanschoren, Pavel Brazdil, Carlos Soares, Lars Kotthoff
1201, 2014
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Algorithm Selection for Combinatorial Search Problems: A Survey
Lars Kotthoff
AI Magazine, 35(3):48-60, 2014
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Integrating Optimisation And Agent-Based Modelling
Peter George Johnson, Tina Balke, Lars Kotthoff
ECMS, 775-781, 2014
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Ranking Algorithms by Performance
Lars Kotthoff
LION, 16-20, 2014
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Algorithm Configuration in the Cloud: A Feasibility Study
Daniel Geschwender, Frank Hutter, Lars Kotthoff, Yuri Malitsky, Holger H. Hoos, Kevin Leyton-Brown
LION, 41-46, 2014
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An Open and Reproducible Paper on Openness and Reproducibility of Papers in Computational Science
Sylwester Arabas, Michael R. Bareford, Ian P. Gent, Benjamin M. Gorman, Masih Hajiarabderkani, Tristan Henderson, Luke Hutton, Alexander Konovalov, Lars Kotthoff, Ciaran McCreesh, Ruma R. Paul, Karen E. Petrie, Abdul Razaq, Daniël Reijsbergen
CoRR, abs/1408.2123, 2014
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Towards an Algorithm Selection Standard: Data Format and Tools
Lars Kotthoff
MetaSel@ECAI, 1, 2014
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Discriminating Instance Generation for Automated Constraint Model Selection
Ian P. Gent, Bilal Syed Hussain, Christopher Jefferson, Lars Kotthoff, Ian Miguel, Glenna F. Nightingale, Peter Nightingale
CP, 356-365, 2014
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Reliability of computational experiments on virtualised hardware
Lars Kotthoff
J. Exp. Theor. Artif. Intell., 26(1):33-49, 2014
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Qualitative modelling via constraint programming
Thomas W. Kelsey, Lars Kotthoff, Christopher Jefferson, Stephen A. Linton, Ian Miguel, Peter Nightingale, Ian P. Gent
Constraints, 19(2):163-173, 2014
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Proteus: A Hierarchical Portfolio of Solvers and Transformations
Barry Hurley 0001, Lars Kotthoff, Yuri Malitsky, Barry O'Sullivan
CPAIOR, 301-317, 2014
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Web-Scale Distributed eScience AI Search across Disconnected and Heterogeneous Infrastructures
Tom Kelsey, Martin McCaffery, Lars Kotthoff
eScience, 39-46, 2014
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Lazy Branching for Constraint Satisfaction
Deepak Mehta, Barry O'Sullivan, Lars Kotthoff, Yuri Malitsky
ICTAI, 1012-1019, 2013
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Proteus: A Hierarchical Portfolio of Solvers and Transformations
Barry Hurley 0001, Lars Kotthoff, Yuri Malitsky, Barry O'Sullivan
CoRR, abs/1306.5606, 2013
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LLAMA: Leveraging Learning to Automatically Manage Algorithms
Lars Kotthoff
CoRR, abs/1306.1031, 2013
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Automated Symmetry Breaking and Model Selection in Conjure
Ozgur Akgun, Alan M. Frisch, Ian P. Gent, Bilal Syed Hussain, Christopher Jefferson, Lars Kotthoff, Ian Miguel, Peter Nightingale
CP, 107-116, 2013
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Ranking Algorithms by Performance
Lars Kotthoff
CoRR, abs/1311.4319, 2013
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The AAAI-13 Conference Workshops
Vikas Agrawal, Christopher Archibald, Mehul Bhatt, Hung Hai Bui, Diane J. Cook, Juan Cortés, Christopher W. Geib, Vibhav Gogate, Hans W. Guesgen, Dietmar Jannach, Michael Johanson, Kristian Kersting, George Konidaris, Lars Kotthoff, Martin Michalowski, Sriraam Natarajan, Barry O'Sullivan, Marc Pickett, Vedran Podobnik, David Poole 0001, Lokendra Shastri, Amarda Shehu, Gita Sukthankar
AI Magazine, 34(4):9-, 2013
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An automated approach to generating efficient constraint solvers
Dharini Balasubramaniam, Christopher Jefferson, Lars Kotthoff, Ian Miguel, Peter Nightingale
ICSE, 661-671, 2012
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An evaluation of machine learning in algorithm selection for search problems
Lars Kotthoff, Ian P. Gent, Ian Miguel
AI Commun., 25(3):257-270, 2012
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Hybrid Regression-Classification Models for Algorithm Selection
Lars Kotthoff
ECAI, 480-485, 2012
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A framework for large-scale distributed AI search across disconnected heterogeneous infrastructures
Lars Kotthoff, Tom Kelsey, Martin McCaffery
CoRR, abs/1209.3487, 2012
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Qualitative Modelling via Constraint Programming: Past, Present and Future
Thomas W. Kelsey, Lars Kotthoff, Christopher Jefferson, Stephen A. Linton, Ian Miguel, Peter Nightingale, Ian P. Gent
CoRR, abs/1209.3916, 2012
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The Semigroups of Order 10
Andreas Distler, Christopher Jefferson, Tom Kelsey, Lars Kotthoff
CP, 883-899, 2012
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Algorithm Selection for Combinatorial Search Problems: A Survey
Lars Kotthoff
CoRR, abs/1210.7959, 2012
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On algorithm selection, with an application to combinatorial search problems
Lars Kotthoff
University of St Andrews, UK, 2012
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Modelling Constraint Solver Architecture Design as a Constraint Problem
Ian P. Gent, Christopher Jefferson, Lars Kotthoff, Ian Miguel
CoRR, abs/1110.6290, 2011
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Dominion: An Architecture-Driven Approach to Generating Efficient Constraint Solvers
Dharini Balasubramaniam, Lakshitha de Silva, Christopher Jefferson, Lars Kotthoff, Ian Miguel, Peter Nightingale
WICSA, 228-231, 2011
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Reliability of Computational Experiments on Virtualised Hardware
Ian P. Gent, Lars Kotthoff
CoRR, abs/1110.6288, 2011
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Exact Closest String as a Constraint Satisfaction Problem
Tom Kelsey, Lars Kotthoff
ICCS, 1062-1071, 2011
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Reliability of Computational Experiments on Virtualised Hardware
Ian P. Gent, Lars Kotthoff
AI for Data Center Management and Cloud Computing, 2011
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A Preliminary Evaluation of Machine Learning in Algorithm Selection for Search Problems
Lars Kotthoff, Ian P. Gent, Ian Miguel
SOCS, 2011
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Learning When to Use Lazy Learning in Constraint Solving
Ian P. Gent, Christopher Jefferson, Lars Kotthoff, Ian Miguel, Neil C. A. Moore, Peter Nightingale, Karen E. Petrie
ECAI, 873-878, 2010
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Ensemble Classification for Constraint Solver Configuration
Lars Kotthoff, Ian Miguel, Peter Nightingale
CP, 321-329, 2010
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Using machine learning to make constraint solver implementation decisions
Lars Kotthoff, Ian P. Gent, Ian Miguel
CoRR, abs/1005.3502, 2010
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Machine learning for constraint solver design -- A case study for the alldifferent constraint
Ian P. Gent, Lars Kotthoff, Ian Miguel, Peter Nightingale
CoRR, abs/1008.4326, 2010
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The Exact Closest String Problem as a Constraint Satisfaction Problem
Tom Kelsey, Lars Kotthoff
CoRR, abs/1005.0089, 2010
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Constraint solvers: An empirical evaluation of design decisions
Lars Kotthoff
CoRR, abs/1002.0134, 2010
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Dominion -- A constraint solver generator
Lars Kotthoff
CoRR, abs/1002.0136, 2010
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Distributed solving through model splitting
Lars Kotthoff, Neil C. A. Moore
CoRR, abs/1008.4328, 2010
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