Lars Kotthoff - RankMe

109 papers A* 5A 9B 4C 1Misc 2Journal 54Unranked 21

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	LLaMEA-SAGE: Guiding Automated Algorithm Design with Structural Feedback from Explainable AI. CoRR Niki van Stein, Anna V. Kononova, Lars Kotthoff, Thomas Bäck
2026	J	`jnl`	mlr3mbo: Bayesian Optimization in R. CoRR Marc Becker, Lennart Schneider, Martin Binder, Lars Kotthoff, Bernd Bischl
2025	J	`jnl`	Best Practices For Empirical Meta-Algorithmic Research: Guidelines from the COSEAL Research Network. CoRR Theresa Eimer, Lennart Schäpermeier, André Biedenkapp, Alexander Tornede, Lars Kotthoff, Pieter Leyman, Matthias Feurer, Katharina Eggensperger, Kaitlin Maile, Tanja Tornede, Anna Kozak, Ke Xue, Marcel Wever, Mitra Baratchi, Damir Pulatov, Heike Trautmann, Haniye Kashgarani, Marius Lindauer
2025	A	`conf`	Code Evolution Graphs: Understanding Large Language Model Driven Design of Algorithms. GECCO Niki van Stein, Anna V. Kononova, Lars Kotthoff, Thomas Bäck
2025	J	`jnl`	Code Evolution Graphs: Understanding Large Language Model Driven Design of Algorithms. CoRR Niki van Stein, Anna V. Kononova, Lars Kotthoff, Thomas Bäck
2025	J	`jnl`	Improving the computational efficiency of stochastic programs using automated algorithm configuration: an application to decentralized energy systems. Ann. Oper. Res. Hannes Schwarz, Lars Kotthoff, Holger H. Hoos, Wolf Fichtner, Valentin Bertsch
2025	J	`jnl`	The third and fourth international competitions on computational models of argumentation: Design, results and analysis. Argument Comput. Stefano Bistarelli, Lars Kotthoff, Jean-Marie Lagniez, Emmanuel Lonca, Jean-Guy Mailly, Julien Rossit, Francesco Santini, Carlo Taticchi
2024	—	`conf`	An Empirical Assessment of Progress in Automated Theorem Proving. IJCAR (1) Geoff Sutcliffe, Christian B. Suttner, Lars Kotthoff, C. Raymond Perrault, Zain Khalid
2024	J	`jnl`	Automated Machine Learning For Computational Mechanics (Dagstuhl Seminar 24282). Dagstuhl Reports Elena Raponi, Lars Kotthoff, Hyunsun Alicia Kim, Marius Lindauer
2024	A*	`conf`	FlexiBO: A Decoupled Cost-Aware Multi-objective Optimization Approach for Deep Neural Networks (Abstract Reprint). AAAI Md Shahriar Iqbal, Jianhai Su, Lars Kotthoff, Pooyan Jamshidi
2024	—	`conf`	Visualization and Automation in Data Science: Exploring the Paradox of Humans-in-the-Loop. VDS@VIS Jen Rogers, Marie Anastacio, Jürgen Bernard, Mehdi Chakhchoukh, Rebecca Faust, Andreas Kerren, Steffen Koch, Lars Kotthoff, Cagatay Turkay, Emily Wall
2023	A	`conf`	Automatic Parallel Portfolio Selection. ECAI Haniye Kashgarani, Lars Kotthoff
2023	J	`jnl`	FlexiBO: A Decoupled Cost-Aware Multi-Objective Optimization Approach for Deep Neural Networks. J. Artif. Intell. Res. Md Shahriar Iqbal, Jianhai Su, Lars Kotthoff, Pooyan Jamshidi
2023	J	`jnl`	Human-Centered Approaches for Provenance in Automated Data Science (Dagstuhl Seminar 23372). Dagstuhl Reports Anamaria Crisan, Lars Kotthoff, Marc Streit, Kai Xu
2022	J	`jnl`	Automated Benchmark-Driven Design and Explanation of Hyperparameter Optimizers. IEEE Trans. Evol. Comput. Julia Moosbauer, Martin Binder, Lennart Schneider, Florian Pfisterer, Marc Becker, Michel Lang, Lars Kotthoff, Bernd Bischl
2022	J	`jnl`	How explainable are adversarially-robust CNNs? CoRR Mehdi Nourelahi, Lars Kotthoff, Peijie Chen, Anh Nguyen
2022	—	`conf`	Opening the Black Box: Automated Software Analysis for Algorithm Selection. AutoML Damir Pulatov, Marie Anastacio, Lars Kotthoff, Holger H. Hoos
2022	—	`conf`	Optimizing Laser-Induced Graphene Production. PAIS@ECAI Lars Kotthoff, Sourin Dey, Jake Heil, Vivek Jain, Todd Muller, Alexander Tyrrell, Hud Wahab, Patrick Johnson
2021	J	`jnl`	Automated Benchmark-Driven Design and Explanation of Hyperparameter Optimizers. CoRR Julia Moosbauer, Martin Binder, Lennart Schneider, Florian Pfisterer, Marc Becker, Michel Lang, Lars Kotthoff, Bernd Bischl
2021	J	`jnl`	Bayesian Optimization in Materials Science: A Survey. CoRR Lars Kotthoff, Hud Wahab, Patrick Johnson
2021	—	`conf`	Is Algorithm Selection Worth It? Comparing Selecting Single Algorithms and Parallel Execution. MetaDL@AAAI Haniye Kashgarani, Lars Kotthoff
2021	J	`jnl`	Modeling and Optimizing Laser-Induced Graphene. CoRR Lars Kotthoff, Sourin Dey, Vivek Jain, Alexander Tyrrell, Hud Wahab, Patrick Johnson
2021	J	`jnl`	Summary Report for the Third International Competition On Computational Models of Argumentation. AI Mag. Stefano Bistarelli, Lars Kotthoff, Francesco Santini, Carlo Taticchi
2021	J	`jnl`	mlr3pipelines - Flexible Machine Learning Pipelines in R. J. Mach. Learn. Res. Martin Binder, Florian Pfisterer, Michel Lang, Lennart Schneider, Lars Kotthoff, Bernd Bischl
2020	—	`conf`	A First Overview of ICCMA'19. AI³@AI*IA Stefano Bistarelli, Lars Kotthoff, Francesco Santini, Carlo Taticchi
2020	J	`jnl`	FlexiBO: Cost-Aware Multi-Objective Optimization of Deep Neural Networks. CoRR Md Shahriar Iqbal, Jianhai Su, Lars Kotthoff, Pooyan Jamshidi
2020	A*	`conf`	Opening the Black Box: Automatically Characterizing Software for Algorithm Selection (Student Abstract). AAAI Damir Pulatov, Lars Kotthoff
2019	—	`ch.`	Auto-WEKA: Automatic Model Selection and Hyperparameter Optimization in WEKA. Automated Machine Learning Lars Kotthoff, Chris Thornton, Holger H. Hoos, Frank Hutter, Kevin Leyton-Brown
2019	—	`book`	Automated Machine Learning - Methods, Systems, Challenges Automated Machine Learning Frank Hutter, Lars Kotthoff, Joaquin Vanschoren
2019	—	`conf`	Hands-On Session with ASlib. AMIR@ECIR Lars Kotthoff
2019	—	`conf`	Preface: The 1st Interdisciplinary Workshop on Algorithm Selection and Meta-Learning in Information Retrieval (AMIR). AMIR@ECIR Joeran Beel, Lars Kotthoff
2019	—	`ed.`	Proceedings of the 1st Interdisciplinary Workshop on Algorithm Selection and Meta-Learning in Information Retrieval co-located with the 41st European Conference on Information Retrieval (ECIR 2019), Cologne, Germany, April 14, 2019. AMIR@ECIR Jöran Beel, Lars Kotthoff
2019	—	`conf`	Proposal for the 1st Interdisciplinary Workshop on Algorithm Selection and Meta-Learning in Information Retrieval (AMIR). ECIR (2) Jöran Beel, Lars Kotthoff
2019	J	`jnl`	The algorithm selection competitions 2015 and 2017. Artif. Intell. Marius Lindauer, Jan N. van Rijn, Lars Kotthoff
2019	—	`conf`	Transfer Learning for Performance Modeling of Deep Neural Network Systems. OpML Md Shahriar Iqbal, Lars Kotthoff, Pooyan Jamshidi
2019	J	`jnl`	Transfer Learning for Performance Modeling of Deep Neural Network Systems. CoRR Md Shahriar Iqbal, Lars Kotthoff, Pooyan Jamshidi
2019	J	`jnl`	mlr3: A modern object-oriented machine learning framework in R. J. Open Source Softw. Michel Lang, Martin Binder, Jakob Richter, Patrick Schratz, Florian Pfisterer, Stefan Coors, Quay Au, Giuseppe Casalicchio, Lars Kotthoff, Bernd Bischl
2018	B	`conf`	A Regression-Based Methodology for Online Algorithm Selection. SOCS Hans Degroote, Patrick De Causmaecker, Bernd Bischl, Lars Kotthoff
2018	—	`conf`	Containerisation and Dynamic Frameworks in ICCMA'19. SAFA Stefano Bistarelli, Lars Kotthoff, Francesco Santini, Carlo Taticchi
2018	J	`jnl`	Leveraging TSP Solver Complementarity through Machine Learning. Evol. Comput. Pascal Kerschke, Lars Kotthoff, Jakob Bossek, Holger H. Hoos, Heike Trautmann
2018	A*	`conf`	Quantifying Algorithmic Improvements over Time. IJCAI Lars Kotthoff, Alexandre Fréchette, Tomasz P. Michalak, Talal Rahwan, Holger H. Hoos, Kevin Leyton-Brown
2018	J	`jnl`	The Algorithm Selection Competition Series 2015-17. CoRR Marius Lindauer, Jan N. van Rijn, Lars Kotthoff
2017	J	`jnl`	Auto-WEKA 2.0: Automatic model selection and hyperparameter optimization in WEKA. J. Mach. Learn. Res. Lars Kotthoff, Chris Thornton, Holger H. Hoos, Frank Hutter, Kevin Leyton-Brown
2017	J	`jnl`	Hot-Rodding the Browser Engine: Automatic Configuration of JavaScript Compilers. CoRR Chris Fawcett, Lars Kotthoff, Holger H. Hoos
2017	—	`conf`	Open Algorithm Selection Challenge 2017: Setup and Scenarios. OASC Marius Lindauer, Jan N. van Rijn, Lars Kotthoff
2017	J	`jnl`	The ICON Challenge on Algorithm Selection. AI Mag. Lars Kotthoff, Barry Hurley, Barry O'Sullivan
2017	J	`jnl`	The Inductive Constraint Programming Loop. IEEE Intell. Syst. Christian Bessiere, Luc De Raedt, Tias Guns, Lars Kotthoff, Mirco Nanni, Siegfried Nijssen, Barry O'Sullivan, Anastasia Paparrizou, Dino Pedreschi, Helmut Simonis
2016	J	`jnl`	ASlib: A benchmark library for algorithm selection. Artif. Intell. Bernd Bischl, Pascal Kerschke, Lars Kotthoff, Marius Lindauer, Yuri Malitsky, Alexandre Fréchette, Holger H. Hoos, Frank Hutter, Kevin Leyton-Brown, Kevin Tierney, Joaquin Vanschoren
2016	—	`ch.`	Advanced Portfolio Techniques. Data Mining and Constraint Programming Barry Hurley, Lars Kotthoff, Yuri Malitsky, Deepak Mehta, Barry O'Sullivan
2016	—	`ch.`	Algorithm Selection for Combinatorial Search Problems: A Survey. Data Mining and Constraint Programming Lars Kotthoff
2016	—	`book`	Data Mining and Constraint Programming - Foundations of a Cross-Disciplinary Approach Data Mining and Constraint Programming Christian Bessiere, Luc De Raedt, Lars Kotthoff, Siegfried Nijssen, Barry O'Sullivan, Dino Pedreschi
2016	—	`ch.`	ICON Loop Carpooling Show Case. Data Mining and Constraint Programming Mirco Nanni, Lars Kotthoff, Riccardo Guidotti, Barry O'Sullivan, Dino Pedreschi
2016	—	`ch.`	ICON Loop Health Show Case. Data Mining and Constraint Programming Barry Hurley, Lars Kotthoff, Barry O'Sullivan, Helmut Simonis
2016	—	`conf`	Portfolios of Subgraph Isomorphism Algorithms. LION Lars Kotthoff, Ciaran McCreesh, Christine Solnon
2016	—	`ed.`	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 AutoML@ICML Frank Hutter, Lars Kotthoff, Joaquin Vanschoren
2016	—	`conf`	Reinforcement Learning for Automatic Online Algorithm Selection - an Empirical Study. ITAT Hans Degroote, Bernd Bischl, Lars Kotthoff, Patrick De Causmaecker
2016	—	`ch.`	The Inductive Constraint Programming Loop. Data Mining and Constraint Programming Christian Bessiere, Luc De Raedt, Tias Guns, Lars Kotthoff, Mirco Nanni, Siegfried Nijssen, Barry O'Sullivan, Anastasia Paparrizou, Dino Pedreschi, Helmut Simonis
2016	A*	`conf`	Using the Shapley Value to Analyze Algorithm Portfolios. AAAI Alexandre Fréchette, Lars Kotthoff, Tomasz P. Michalak, Talal Rahwan, Holger H. Hoos, Kevin Leyton-Brown
2016	J	`jnl`	mlr Tutorial. CoRR 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
2016	J	`jnl`	mlr: Machine Learning in R. J. Mach. Learn. Res. Bernd Bischl, Michel Lang, Lars Kotthoff, Julia Schiffner, Jakob Richter, Erich Studerus, Giuseppe Casalicchio, Zachary M. Jones
2015	J	`jnl`	ASlib: A Benchmark Library for Algorithm Selection. CoRR Bernd Bischl, Pascal Kerschke, Lars Kotthoff, Marius Lindauer, Yuri Malitsky, Alexandre Fréchette, Holger H. Hoos, Frank Hutter, Kevin Leyton-Brown, Kevin Tierney, Joaquin Vanschoren
2015	A	`conf`	Find Your Way Back: Mobility Profile Mining with Constraints. CP Lars Kotthoff, Mirco Nanni, Riccardo Guidotti, Barry O'Sullivan
2015	J	`jnl`	ICON Challenge on Algorithm Selection. CoRR Lars Kotthoff
2015	—	`conf`	Improving the State of the Art in Inexact TSP Solving Using Per-Instance Algorithm Selection. LION Lars Kotthoff, Pascal Kerschke, Holger H. Hoos, Heike Trautmann
2015	J	`jnl`	On Algorithm Selection, with an application to combinatorial search problems. Constraints An Int. J. Lars Kotthoff
2015	—	`ed.`	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. MetaSel@PKDD/ECML Joaquin Vanschoren, Pavel Brazdil, Christophe G. Giraud-Carrier, Lars Kotthoff
2015	J	`jnl`	The Inductive Constraint Programming Loop. CoRR Christian Bessiere, Luc De Raedt, Tias Guns, Lars Kotthoff, Mirco Nanni, Siegfried Nijssen, Barry O'Sullivan, Anastasia Paparrizou, Dino Pedreschi, Helmut Simonis
2015	J	`jnl`	Top Tips to Make Your Research Irreproducible. CoRR Neil P. Chue Hong, Tom Crick, Ian P. Gent, Lars Kotthoff, Kenji Takeda
2014	—	`conf`	Algorithm Configuration in the Cloud: A Feasibility Study. LION Daniel Geschwender, Frank Hutter, Lars Kotthoff, Yuri Malitsky, Holger H. Hoos, Kevin Leyton-Brown
2014	J	`jnl`	Algorithm Selection for Combinatorial Search Problems: A Survey. AI Mag. Lars Kotthoff
2014	J	`jnl`	An Open and Reproducible Paper on Openness and Reproducibility of Papers in Computational Science. CoRR 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
2014	A	`conf`	Discriminating Instance Generation for Automated Constraint Model Selection. CP Ian P. Gent, Bilal Syed Hussain, Christopher Jefferson, Lars Kotthoff, Ian Miguel, Glenna F. Nightingale, Peter Nightingale
2014	C	`conf`	Integrating Optimisation And Agent-Based Modelling. ECMS Peter George Johnson, Tina Balke, Lars Kotthoff
2014	—	`ed.`	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. MetaSel@ECAI Joaquin Vanschoren, Pavel Brazdil, Carlos Soares, Lars Kotthoff
2014	B	`conf`	Proteus: A Hierarchical Portfolio of Solvers and Transformations. CPAIOR Barry Hurley, Lars Kotthoff, Yuri Malitsky, Barry O'Sullivan
2014	J	`jnl`	Qualitative modelling via constraint programming. Constraints An Int. J. Thomas W. Kelsey, Lars Kotthoff, Christopher Jefferson, Stephen A. Linton, Ian Miguel, Peter Nightingale, Ian P. Gent
2014	—	`conf`	Ranking Algorithms by Performance. LION Lars Kotthoff
2014	Misc	`conf`	Recomputation.org: Experiences of Its First Year and Lessons Learned. UCC Ian P. Gent, Lars Kotthoff
2014	J	`jnl`	Reliability of computational experiments on virtualised hardware. J. Exp. Theor. Artif. Intell. Lars Kotthoff
2014	—	`conf`	Towards an Algorithm Selection Standard: Data Format and Tools. MetaSel@ECAI Lars Kotthoff
2014	—	`conf`	Web-Scale Distributed eScience AI Search across Disconnected and Heterogeneous Infrastructures. eScience Tom W. Kelsey, Martin McCaffery, Lars Kotthoff
2013	A	`conf`	Automated Symmetry Breaking and Model Selection in Conjure. CP Ozgur Akgun, Alan M. Frisch, Ian P. Gent, Bilal Syed Hussain, Christopher Jefferson, Lars Kotthoff, Ian Miguel, Peter Nightingale
2013	J	`jnl`	LLAMA: Leveraging Learning to Automatically Manage Algorithms. CoRR Lars Kotthoff
2013	B	`conf`	Lazy Branching for Constraint Satisfaction. ICTAI Deepak Mehta, Barry O'Sullivan, Lars Kotthoff, Yuri Malitsky
2013	J	`jnl`	Proteus: A Hierarchical Portfolio of Solvers and Transformations. CoRR Barry Hurley, Lars Kotthoff, Yuri Malitsky, Barry O'Sullivan
2013	J	`jnl`	Ranking Algorithms by Performance. CoRR Lars Kotthoff
2013	J	`jnl`	The AAAI-13 Conference Workshops. AI Mag. Vikas Agrawal, Christopher Archibald, Mehul Bhatt, Hung Bui, Diane J. Cook, Juan Cortés, Christopher W. Geib, Vibhav Gogate, Hans W. Guesgen, Dietmar Jannach, Michael Johanson, Kristian Kersting, George Dimitri Konidaris, Lars Kotthoff, Martin Michalowski, Sriraam Natarajan, Barry O'Sullivan, Marc Pickett, Vedran Podobnik, David Poole, Lokendra Shastri, Amarda Shehu, Gita Sukthankar
2012	J	`jnl`	A framework for large-scale distributed AI search across disconnected heterogeneous infrastructures CoRR Lars Kotthoff, Tom W. Kelsey, Martin McCaffery
2012	J	`jnl`	Algorithm Selection for Combinatorial Search Problems: A Survey CoRR Lars Kotthoff
2012	A*	`conf`	An automated approach to generating efficient constraint solvers. ICSE Dharini Balasubramaniam, Christopher Jefferson, Lars Kotthoff, Ian Miguel, Peter Nightingale
2012	J	`jnl`	An evaluation of machine learning in algorithm selection for search problems. AI Commun. Lars Kotthoff, Ian P. Gent, Ian Miguel
2012	A	`conf`	Hybrid Regression-Classification Models for Algorithm Selection. ECAI Lars Kotthoff
2012	—	`—`	On algorithm selection, with an application to combinatorial search problems. Lars Kotthoff
2012	J	`jnl`	Qualitative Modelling via Constraint Programming: Past, Present and Future CoRR Thomas W. Kelsey, Lars Kotthoff, Christopher Jefferson, Stephen A. Linton, Ian Miguel, Peter Nightingale, Ian P. Gent
2012	A	`conf`	The Semigroups of Order 10. CP Andreas Distler, Christopher Jefferson, Tom W. Kelsey, Lars Kotthoff
2011	B	`conf`	A Preliminary Evaluation of Machine Learning in Algorithm Selection for Search Problems. SOCS Lars Kotthoff, Ian P. Gent, Ian Miguel
2011	—	`conf`	Dominion: An Architecture-Driven Approach to Generating Efficient Constraint Solvers. WICSA Dharini Balasubramaniam, Lakshitha de Silva, Christopher Jefferson, Lars Kotthoff, Ian Miguel, Peter Nightingale
2011	Misc	`conf`	Exact Closest String as a Constraint Satisfaction Problem. ICCS Tom W. Kelsey, Lars Kotthoff
2011	J	`jnl`	Modelling Constraint Solver Architecture Design as a Constraint Problem CoRR Ian P. Gent, Christopher Jefferson, Lars Kotthoff, Ian Miguel
2011	J	`jnl`	Reliability of Computational Experiments on Virtualised Hardware CoRR Ian P. Gent, Lars Kotthoff
2011	—	`conf`	Reliability of Computational Experiments on Virtualised Hardware. AI for Data Center Management and Cloud Computing Ian P. Gent, Lars Kotthoff
2010	J	`jnl`	Constraint solvers: An empirical evaluation of design decisions CoRR Lars Kotthoff
2010	J	`jnl`	Distributed solving through model splitting CoRR Lars Kotthoff, Neil C. A. Moore
2010	J	`jnl`	Dominion -- A constraint solver generator CoRR Lars Kotthoff
2010	A	`conf`	Ensemble Classification for Constraint Solver Configuration. CP Lars Kotthoff, Ian Miguel, Peter Nightingale
2010	A	`conf`	Learning When to Use Lazy Learning in Constraint Solving. ECAI Ian P. Gent, Christopher Jefferson, Lars Kotthoff, Ian Miguel, Neil C. A. Moore, Peter Nightingale, Karen E. Petrie
2010	J	`jnl`	Machine learning for constraint solver design -- A case study for the alldifferent constraint CoRR Ian P. Gent, Lars Kotthoff, Ian Miguel, Peter Nightingale
2010	J	`jnl`	The Exact Closest String Problem as a Constraint Satisfaction Problem CoRR Tom W. Kelsey, Lars Kotthoff
2010	J	`jnl`	Using machine learning to make constraint solver implementation decisions CoRR Lars Kotthoff, Ian P. Gent, Ian Miguel