Publications
2022
- Anna L.D. Latour, Behrouz Babaki, Daniël Fokkinga, Marie Anastacio, Holger H. Hoos and Siegfried Nijssen.
Exact stochastic constraint optimisation with applications in network analysis.Artificial Intelligence, 304:103650, 2022.
2021
- Holger H Hoos, Frank Hutter and Kevin Leyton-Brown.
Automated Configuration and Selection of SAT Solvers.In Handbook of Satisfiability, pages 481–507. IOS Press, 2021.
- Koen van der Blom, Alex Serban, Holger Hoos and Joost Visser.
AutoML Adoption in ML Software.In 8th ICML Workshop on Automated Machine Learning. 2021.
- Bruno Veloso, Luciano Caroprese, Matthias König, Sónia Teixeira, Giuseppe Manco, Holger H Hoos and Jo~ao Gama.
Hyper-Parameter Optimization for Latent Spaces in Dynamic Recommender Systems.In Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. 2021.
- Nelly Rosaura Palacios Salinas, Mitra Baratchi, Jan N. van Rijn and Andreas Vollrath.
Automated Machine Learning for Satellite Data: Integrating Remote Sensing Pre-trained Models into AutoML Systems.In Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. 2021.
- Gilles Ottervanger, Mitra Baratchi and Holger H Hoos.
MultiETSC: automated machine learning for early time series classification.Data Mining and Knowledge Discovery, 35(6):2602–2654, 2021.
- Matthias König, Holger H Hoos and Jan N van Rijn.
Speeding Up Neural Network Verification via Automated Algorithm Configuration.In ICLR Workshop on Security and Safety in Machine Learning Systems. 2021.
- Wessel A. van Eeden, Chuan Luo, Albert M. van Hemert, Ingrid V.E. Carlier, Brenda W. Penninx, Klaas J. Wardenaar, Holger Hoos and Erik J. Giltay.
Predicting the 9-year course of mood and anxiety disorders with automated machine learning: A comparison between auto-sklearn, naïve Bayes classifier, and traditional logistic regression.Psychiatry Research, 299:113823, 2021.
- Andreas Dengel, Oren Etzioni, Nicole DeCario, Holger Hoos, Fei-Fei Li, Junichi Tsujii and Paolo Traverso. Next Big Challenges in Core AI Technology, pages 90–115. Springer International Publishing, Cham, 2021.
- Alex Serban, Koen van der Blom, Holger Hoos and Joost Visser.
Practices for Engineering Trustworthy Machine Learning Applications.In IEEE/ACM 1st Workshop on AI Engineering-Software Engineering for AI (WAIN), 97–100. IEEE, 2021.
- Nuno César de Sá, Mitra Baratchi, Leon T. Hauser and Peter van Bodegom.
Exploring the Impact of Noise on Hybrid Inversion of PROSAIL RTM on Sentinel-2 Data.Remote Sensing, 2021.
- Sjonnie Boonstra, Koen van der Blom, Hèrm Hofmeyer and Michael T. M. Emmerich.
Hybridization of an evolutionary algorithm and simulations of co-evolutionary design processes for early-stage building spatial design optimization.Automation in Construction, 124:103522, 2021.
- Mike Huisman, Jan N. van Rijn and Aske Plaat.
A Survey of Deep Meta-Learning.Artificial Intelligence Review, pages 1–59, 2021.
- Matthias Feurer, Jan N. van Rijn, Arlind Kadra, Pieter Gijsbers, Neeratyoy Mallik, Sahithya Ravi, Andreas Müller, Joaquin Vanschoren and Frank Hutter.
OpenML-Python: an extensible Python API for OpenML.Journal of Machine Learning Research, 22(100):1–5, 2021.
- Marie Anastacio.
Greybox Algorithm Configuration.In Zhi-Hua Zhou, editor, Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, IJCAI 2021, Virtual Event / Montreal, Canada, 19-27 August 2021, 4875–4876. ijcai.org, 2021.
- Théo Matricon, Marie Anastacio, Nathanaël Fijalkow, Laurent Simon and Holger H. Hoos.
Statistical Comparison of Algorithm Performance Through Instance Selection.In Laurent D. Michel, editor, 27th International Conference on Principles and Practice of Constraint Programming, CP 2021, Montpellier, France (Virtual Conference), October 25-29, 2021, volume 210 of LIPIcs, 43:1–43:21. Schloss Dagstuhl - Leibniz-Zentrum f"ur Informatik, 2021.
2020
- Anna L. D. Latour, Behrouz Babaki, Daniël Fokkinga, Marie Anastacio, Holger H. Hoos and Siegfried Nijssen.
Stochastic Constraint Optimisation with Applications in Network Analysis (extended abstract).In International Workshop on Model Counting (MCW), in conjunction with SAT 2020. jul 2020.
- Chuan Luo, Holger Hoos and Shaowei Cai.
PbO-CCSAT: Boosting Local Search for Satisfiability Using Programming by Optimisation.In Thomas Bäck, Mike Preuss, André Deutz, Hao Wang, Carola Doerr, Michael Emmerich and Heike Trautmann, editors, Parallel Problem Solving from Nature – PPSN XVI, 373–389. Cham, 2020. Springer International Publishing.
- Z. Akata, D. Balliet, M. de Rijke, F. Dignum, V. Dignum, G. Eiben, A. Fokkens, D. Grossi, K. Hindriks, H. Hoos, H. Hung, C. Jonker, C. Monz, M. Neerincx, F. Oliehoek, H. Prakken, S. Schlobach, L. van der Gaag, F. van Harmelen, H. van Hoof, B. van Riemsdijk, A. van Wynsberghe, R. Verbrugge, B. Verheij, P. Vossen and M. Welling.
A Research Agenda for Hybrid Intelligence: Augmenting Human Intellect With Collaborative, Adaptive, Responsible, and Explainable Artificial Intelligence.Computer, 53(8):18–28, 2020.
- Yasha Pushak and Holger H. Hoos.
Golden Parameter Search: Exploiting Structure to Quickly Configure Parameters in Parallel.In Proceedings of the 2020 Genetic and Evolutionary Computation Conference, GECCO '20, 245–253. New York, NY, USA, 2020. Association for Computing Machinery.
- Yasha Pushak and Holger H. Hoos.
Advanced Statistical Analysis of Empirical Performance Scaling.In Proceedings of the 2020 Genetic and Evolutionary Computation Conference, GECCO '20, 236–244. New York, NY, USA, 2020. Association for Computing Machinery.
- Lindsey Burggraaff, Eelke B. Lenselink, Willem Jespers, Jesper van Engelen, Brandon J. Bongers, Marina Gorostiola González, Rongfang Liu, Holger H. Hoos, Herman W. T. van Vlijmen, Adriaan P. IJzerman and Gerard J. P. van Westen.
Successive Statistical and Structure-Based Modeling to Identify Chemically Novel Kinase Inhibitors.Journal of Chemical Information and Modeling, 60(9):4283–4295, 2020. PMID: 32343143.
- Yasha Pushak, Zongxu Mu and Holger H Hoos.
Empirical scaling analyzer: An automated system for empirical analysis of performance scaling.AI Communications, pages 1–19, 2020.
- Sam Bayless, Nodir Kodirov, Syed M. Iqbal, Ivan Beschastnikh, Holger H. Hoos and Alan J. Hu.
Scalable constraint-based virtual data center allocation.Artificial Intelligence, 278:103196, 2020.
- Jan H. van Staalduinen, Jaco Tetteroo, Daniela Gawehns and Mitra Baratchi.
An Intelligent Tree Planning Approach Using Location-based Social Networks Data.In Pre-proceedings of BNAIC/BeneLearn 2020, 284–297. 2020.
- Matthias König, Holger H Hoos and Jan N van Rijn.
Towards Algorithm-Agnostic Uncertainty Estimation: Predicting Classification Error in an Automated Machine Learning Setting.In ICML Workshop on Automated Machine Learning. 2020.
- Koen van der Blom, Timo M. Deist, Tea Tušar, Mariapia Marchi, Yusuke Nojima, Akira Oyama, Vanessa Volz and Boris Naujoks.
Towards Realistic Optimization Benchmarks: A Questionnaire on the Properties of Real-World Problems.In Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion, GECCO '20, 293–294. New York, NY, USA, 2020. ACM.
- Jeroen G. Rook, Anna L. D. Latour, Siegfried Nijssen and Holger H. Hoos.
Better Caching for Better Model Counting.In International Workshop on Model Counting (MCW), in conjunction with SAT 2020. jul 2020.
- Laurens Arp, Dyon van Vreumingen, Daniela Gawehns and Mitra Baratchi.
Dynamic macro scale traffic flow optimisation using crowd-sourced urban movement data.In 2020 21st IEEE International Conference on Mobile Data Management (MDM), 168–177. IEEE, 2020.
- Bram M. Renting, Holger H. Hoos and Catholijn M. Jonker.
Automated Configuration of Negotiation Strategies.In Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems, 1116–1124. Auckland, 2020. International Foundation for Autonomous Agents and Multiagent Systems.
- Joao Mendes-Moreira and Mitra Baratchi.
Reconciling predictions in the regression setting: an application to bus travel time prediction.In International Symposium on Intelligent Data Analysis, 313–325. Springer, 2020.
- Alex Serban, Koen van der Blom, Holger Hoos and Joost Visser.
Adoption and Effects of Software Engineering Best Practices in Machine Learning.In Proceedings of the 14th ACM / IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM), ESEM '20. New York, NY, USA, 2020. ACM.
- Marie Anastacio and Holger Hoos.
Model-Based Algorithm Configuration with Default-Guided Probabilistic Sampling.In Proceedings of the 16th International Conference on Parallel Problem Solving from Nature (PPSN-20). 2020.
- Marie Anastacio and Holger Hoos.
Combining Sequential Model-Based Algorithm Configuration with Default-Guided Probabilistic Sampling.In Genetic and Evolutionary Computation Conference Companion (GECCO '20 Companion), July 8–12, 2020, Cancún, Mexico. ACM, 2020.
- Jeannette Shijie Ma, Marcello A Gómez Maureira and Jan N van Rijn.
Eating Sound Dataset for 20 Food Types and Sound Classification Using Convolutional Neural Networks.In Companion Publication of the 2020 International Conference on Multimodal Interaction, 348–351. 2020.
- Sjonnie Boonstra, Koen van der Blom, Hèrm Hofmeyer and Michael T. M. Emmerich.
Conceptual Structural System Layouts via Design Response Grammars and Evolutionary Algorithms.Automation in Construction, 116:103009, 2020.
- Hossein A Rahmani, Mohammad Aliannejadi, Mitra Baratchi and Fabio Crestani.
Joint Geographical and Temporal Modeling based on Matrix Factorization for Point-of-Interest Recommendation.In Proceedings of 42d European Conference on Information Retrieval. 2020.
2019
- Anna Louise D. Latour, Behrouz Babaki and Siegfried Nijssen.
Stochastic Constraint Propagation for Mining Probabilistic Networks.In Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, IJCAI-19, 1137–1145. International Joint Conferences on Artificial Intelligence Organization, 7 2019.
- Marius Lindauer, Jan N van Rijn and Lars Kotthoff.
The algorithm selection competitions 2015 and 2017.Artificial Intelligence, 272:86–100, 2019.
- Noureddin Sadawi, Ivan Olier, Joaquin Vanschoren, Jan N Van Rijn, Jeremy Besnard, Richard Bickerton, Crina Grosan, Larisa Soldatova and Ross D King.
Multi-task learning with a natural metric for quantitative structure activity relationship learning.Journal of Cheminformatics, 11(1):68, 2019.
- Abhinav Sharma, Jan N van Rijn, Frank Hutter and Andreas Müller.
Hyperparameter Importance for Image Classification by Residual Neural Networks.In International Conference on Discovery Science, 112–126. Springer, 2019.
- Koen van der Blom, Sjonnie Boonstra, Hèrm Hofmeyer and Michael T. M. Emmerich.
Analysing Optimisation Data for Multicriteria Building Spatial Design.In Kalyanmoy Deb, Erik Goodman, Carlos A. Coello Coello, Kathrin Klamroth, Kaisa Miettinen, Sanaz Mostaghim and Patrick Reed, editors, Evolutionary Multi-Criterion Optimization, 671–682. Cham, 2019. Springer International Publishing.
- Sjonnie Boonstra, Koen van der Blom, Hérm Hofmeyer and Michael T. M. Emmerich.
Co-Evolutionary Design Processes Applied to Building Spatial Design Optimization.In Advances in Structural and Multidisciplinary Optimization. Proceedings of the 13th World Congress of Structural and Multidisciplinary Optimization (WCSMO13), 110–115. 2019.
- Can Wang, Thomas Bäck, Holger H. Hoos, Mitra Baratchi, Steffen Limmer and Markus Olhofer.
Automated Machine Learning for Short-term Electric Load Forecasting.In IEEE Symposium Series on Computational Intelligence, SSCI 2019, Xiamen, China, December 6-9, 2019, 314–321. IEEE, 2019.
- Bernd Meijerink, Mitra Baratchi and Geert Heijenk.
Design & analysis of a distributed routing algorithm towards Internet-wide geocast.Computer Communications, 146:201 – 218, 2019.
- Juliane Adrian, Martyn Amos, Mitra Baratchi, Mira Beermann, Nikolai Bode, Maik Boltes, Alessandro Corbetta, Guillaume Dezecache, John Drury, Zhijian Fu and others.
A glossary for research on human crowd dynamics.Collective Dynamics, 4(A19):1–13, 2019.
- Hossein A Rahmani, Mohammad Aliannejadi, Sajad Ahmadian, Mitra Baratchi, Mohsen Afsharchi and Fabio Crestani.
LGLMF: local geographical based logistic matrix factorization model for POI recommendation.In proceedings of The 15th Asia Information Retrieval Societies Conference. 2019.
- Hossein A. Rahmani, Mohammad Aliannejadi, Rasoul Mirzaei Zadeh, Mitra Baratchi, Mohsen Afsharchi and Fabio Crestani.
Category-Aware Location Embedding for Point-of-Interest Recommendation.In Proceedings of the 2019 ACM SIGIR International Conference on Theory of Information Retrieval, ICTIR 19, 173–176. New York, NY, USA, 2019. Association for Computing Machinery.
- Hannes Schwarz, Lars Kotthoff, Holger Hoos, Wolf Fichtner and Valentin Bertsch.
Improving the computational efficiency of stochastic programs using automated algorithm configuration: an application to decentralized energy systems.Annals of Operations Research, pages 1–22, 01 2019.
- F. Schut, J. N. van Rijn and H. Hoos.
Towards Automated Technical Analysis forForeign Exchange Data.In Automating Data Science @ ECML/PKDD. 2019.
- Tijl De Bie, Luc De Raedt, Holger H. Hoos and Padhraic Smyth.
Automating Data Science (Dagstuhl Seminar 18401).Dagstuhl Reports, 8(9):154–181, 2019.
- Lars Kotthoff, Chris Thornton, Holger H. Hoos, Frank Hutter and Kevin Leyton-Brown. Auto-WEKA: Automatic Model Selection and Hyperparameter Optimization in WEKA. The Springer Series on Challenges in Machine Learning. Springer, 2019.
- Chuan Luo, Holger H. Hoos, Shaowei Cai, Qingwei Lin, Hongyu Zhang and Dongmei Zhang.
Local Search with Efficient Automatic Configuration for Minimum Vertex Cover.In Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, IJCAI 2019, Macao, China, August 10-16, 2019, 1297–1304. 2019.
- Camille Pageau, Aymeric Blot, Holger Hoos, Marie-Eléonore Kessaci and Laetitia Jourdan.
A Dynamic Algorithm Framework to Automatically Design a Multi-Objective Local Search.In ROADEF 2019. Le Havre, France, February 2019.
- Jesper E. van Engelen and Holger H. Hoos.
A survey on semi-supervised learning.Machine Learning, Nov 2019.
- Camille Pageau, Aymeric Blot, Holger H. Hoos, Marie-Éléonore Kessaci-Marmion and Laetitia Jourdan.
Configuration of a Dynamic MOLS Algorithm for Bi-objective Flowshop Scheduling.In Proceedings of the 10th International Conference on Evolutionary Multi-Criterion Optimization (EMO 2019), (12 manuscript pages). 2019.
- Pascal Kerschke, Holger H Hoos, Frank Neumann and Heike Trautmann.
Automated Algorithm Selection: Survey and Perspectives.Evolutionary Computation, 27:3–45, 2019.
- Aymeric Blot, Marie-Éléonore Kessaci-Marmion, Laetitia Jourdan and Holger H. Hoos.
Automatic Configuration of Multi-Objective Local Search Algorithms for Permutation Problems.Evolutionary Computation, pages (24 manuscript pages), 2019.
- Marie Anastacio, Chuan Luo and Holger Hoos.
Exploitation of Default Parameter Values in Automated Algorithm Configuration.In Workshop Data Science meets Optimisation (DSO), IJCAI 2019. aug 2019.
- Daniël Fokkinga, Anna Louise D. Latour, Marie Anastacio, Siegfried Nijssen and Holger Hoos.
Programming a Stochastic Constraint Optimisation Algorithm, by Optimisation.In Workshop Data Science meets Optimisation (DSO), IJCAI 2019. aug 2019.
2018
- Salisu Mamman Abdulrahman, Pavel Brazdil, Jan N van Rijn and J Joaquin Vanschoren.
Speeding up algorithm selection using average ranking and active testing by introducing runtime.Machine Learning, 107(1):79–108, 2018.
- Jan N van Rijn, Frank W Takes and Jonathan K Vis.
Computing and Predicting Winning Hands in the Trick-Taking Game of Klaverjas.In Benelux Conference on Artificial Intelligence, 106–120. Springer, 2018.
- Jan N. van Rijn and Frank Hutter.
Hyperparameter Importance Across Datasets.In Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2367–2376. 2018.
- Jan N. van Rijn, Geoffrey Holmes, Bernhard Pfahringer and Joaquin Vanschoren.
The online performance estimation framework: heterogeneous ensemble learning for data streams.Machine Learning, 107(1):149–176, 2018.
- Jan N. van Rijn, Florian Pfisterer, Janek Thomas, Andreas Muller, Bernd Bischl and J. Vanschoren.
Meta learning for defaults: symbolic defaults.In Neural Information Processing Workshop on Meta-Learning. 2018.
- Zongxu Mu, Jérémie Dubois-Lacoste, Holger H. Hoos and Thomas Stützle.
On the Empirical Scaling of Running Time for Finding Optimal Solutions to the TSP.Journal of Heuristics, 6:879–898, 2018.
- Aymeric Blot, Holger H. Hoos, Marie-Éléonore Kessaci-Marmion and Laetitia Jourdan.
Automatic Configuration of Multi-objective Optimization Algorithms. Impact of Correlation between Objectives.In Proceedings of the 30th International Conference on Tools with Artificial Intelligence (ICTAI 2018), (8 manuscript pages). 2018.
- Julieta Martinez, Shobhit Zakhmi, Holger H. Hoos and James J. Little.
LSQ++: Lower Running Time and Higher Recall in Multi-codebook Quantization.In Proceedings of the 15th European Conference on Computer Vision (ECCV 2018), 508–523. 2018.
- Yasha Pushak and Holger H. Hoos.
Algorithm Configuration Landscapes: More Benign than Expected?.In Proceedings of the 15th International Conference on Parallel Problem Solving from Nature (PPSN-18), 271–283. 2018. This paper won the PPSN-18 Best Paper Award.
- Holger H. Hoos, Tomáš Peitl, Friedrich Slivovsky and Stefan Szeider.
Portfolio-Based Algorithm Selection for Circuit QBFs.In John Hooker, editor, Proceedings of the 24th International Conference on Principles and Practice of Constraint Programming (CP 2018), 195–209. Springer International Publishing, 2018.
- Nodir Kodirov, Sam Bayless, Fabian Ruffy, Ivan Beschastnikh, Holger H. Hoos and Alan J. Hu.
VNF chain abstraction for cloud service providers (poster abstract).In Proceedings of the 2018 Symposium on Architectures for Networking and Communications Systems (ANCS-18), 165–166. 2018.
- Nodir Kodirov, Sam Bayless, Fabian Ruffy, Ivan Beschastnikh, Holger H. Hoos and Alan J. Hu.
VNF chain allocation and management at data center scale.In Proceedings of the 2018 Symposium on Architectures for Networking and Communications Systems (ANCS-18), 125–140. 2018.
- Lars Kotthoff, Alexandre Fréchette, Tomasz P. Michalak, Talal Rahwan, Holger H. Hoos and Kevin Leyton-Brown.
Quantifying Algorithmic Improvements over Time.In Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI-18), 5165–5171. 2018.
- Marius Lindauer, Holger Hoos, Frank Hutter and Kevin Leyton-Brown. Selection and Configuration of Parallel Portfolios, pages 583–615. Springer International Publishing, 2018.
- Katharina Eggensperger, Marius Thomas Lindauer, Holger H. Hoos, Frank Hutter and Kevin Leyton-Brown.
Efficient Benchmarking of Algorithm Configuration Procedures via Model-Based Surrogates.Machine Learning, 107:15–41, 2018.
- Pascal Kerschke, Lars Kotthoff, Jakob Bossek, Holger H. Hoos and Heike Trautmann.
Leveraging TSP Solver Complementarity through Machine Learning.Evolutionary Computation, 26:597–620, 2018.
- Benjamin Strang, Peter van der Putten, Jan N. van Rijn and Frank Hutter.
Don't Rule Out Simple Models Prematurely: A Large Scale Benchmark Comparing Linear and Non-linear Classifiers in OpenML.In International Symposium on Intelligent Data Analysis, 303–315. 2018.
- Cristian Chilipirea, Ciprian Dobre, Mitra Baratchi and Maarten van Steen.
Identifying Movements in Noisy Crowd Analytics Data.In 19th IEEE International Conference on Mobile Data Management, 515–520. 2018.
- Cristian Chilipirea, Ciprian Dobre, Mitra Baratchi and Maarten van Steen.
Identifying Stops and Moves in WiFi Tracking Data.Sensors, 18(11):4039, 2018.
- Andrea F. Bocchese, Chris Fawcett, Mauro Vallati, Alfonso Emilio Gerevini and Holger H. Hoos.
Performance robustness of AI planners in the 2014 International Planning Competition.AI Communications, 31(6):445–463, 2018.
2017
- Chris Cameron, Holger H. Hoos, Kevin Leyton-Brown and Frank Hutter.
OASC-2017: *Zilla Submission.In Marius Lindauer, Jan N. van Rijn and Lars Kotthoff, editors, Proceedings of the Open Algorithm Selection Challenge, volume 79 of Proceedings of Machine Learning Research, 15–18. Brussels, Belgium, 11–12 Sep 2017. PMLR.
- Sam Bayless, Nodir Kodirov, Ivan Beschastnikh, Holger H. Hoos and Alan J. Hu.
Scalable Constraint-based Virtual Data Center Allocation.In Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI-17), 546–554. 2017.
- Chris Fawcett, Lars Kotthoff and Holger H. Hoos.
Hot-Rodding the Browser Engine: Automatic Configuration of JavaScript Compilers.CoRR, 2017.
- Leslie Pérez Cáceres, Manuel López-Ibánez, Holger Hoos and Thomas Stützle.
An Experimental Study of Adaptive Capping in irace.In Proceedings of the 11th International Conference on Learning and Intelligent Optimization (LION 11), volume 10556 of Lecture Notes in Computer Science, 235–250. Springer, 2017.
- Aymeric Blot, Alexis Pernet, Laetitia Jourdan, Marie-Éléonore Kessaci-Marmion and Holger H. Hoos.
Automatically Configuring Multi-objective Local Search Using Multi-objective Optimisation.In Proceedings of the 9th International Conference on Evolutionary Multi-Criterion Optimization (EMO 2017), volume 10173 of Lecture Notes in Computer Science, 61–76. Springer, 2017.
- Marius Lindauer, Holger H. Hoos, Kevin Leyton-Brown and Torsten Schaub.
Automatic construction of parallel portfolios via algorithm configuration.Artificial Intelligence, 244:272–290, 2017.
- Mattia Rizzini, Chris Fawcett, Mauro Vallati, Alfonso Emilio Gerevini and Holger H. Hoos.
Static and Dynamic Portfolio Methods for Optimal Planning: An Empirical Analysis.International Journal on Artificial Intelligence Tools, 26(1):1–27, 2017.
- Frank Hutter, Marius Lindauer, Adrian Balint, Sam Bayless, Holger H. Hoos and Kevin Leyton-Brown.
The Configurable SAT Solver Challenge (CSSC).Artificial Intelligence, 243:1–25, 2017.
- Holger H. Hoos, Frank Neumann and Heike Trautmann.
Automated Algorithm Selection and Configuration (Dagstuhl Seminar 16412).Dagstuhl Reports, 6(10):33–74, 2017.
- Lars Kotthoff, Chris Thornton, Holger H. Hoos, Frank Hutter and Kevin Leyton-Brown.
Auto-WEKA 2.0: Automatic model selection and hyperparameter optimization in WEKA.Journal of Machine Learning Research, 18:25:1–25:5, 2017.
- Andre Biedenkapp, Marius Thomas Lindauer, Katharina Eggensperger, Frank Hutter, Chris Fawcett and Holger H. Hoos.
Efficient Parameter Importance Analysis via Ablation with Surrogates.In Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI-17), 773–779. AAAI Press, 2017.
- Marius Lindauer, Frank Hutter, Holger H. Hoos and Torsten Schaub.
AutoFolio: An Automatically Configured Algorithm Selector (Extended Abstract).In Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI-17), 5025–5029. 2017.
- Mitra Baratchi, Geert Heijenk and Maarten van Steen.
Spaceprint: A Mobility-based Fingerprinting Scheme for Spaces.In Proceedings of the 25th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, 102:1–4. 2017.
- Tristan Brugman, Mitra Baratchi, Geert Heijenk and Maarten van Steen.
Inferring the Social-Connectedness of Locations from Mobility Data.In Social Informatics, 443–457. 2017.
- Mozhdeh Gholibeigi, Nora Sarrionandia, Morteza Karimzadeh, Mitra Baratchi, Hans van den Berg and Geert Heijenk.
Reliable Vehicular Broadcast Using 5G Device-to-device Communication.In 2017 10th IFIP Wireless and Mobile Networking Conference (WMNC), 1–8. 2017.
- Bernd Meijerink, Mitra Baratchi and Geert Heijenk.
Evaluation of Geocast Routing Trees on Random and Actual Networks.In Wired/Wireless Internet Communications, 127–142. 2017.
- Andreea-Cristina Petre, Cristian Chilipirea, Mitra Baratchi, Ciprian Dobre and Maarten van Steen.
WiFi Tracking of Pedestrian Behavior.In Smart Sensors Networks, pages 309 – 337. Academic Press, 2017.
2016
- Ashiqur R. KhudaBukhsh, Lin Xu, Holger H. Hoos and Kevin Leyton-Brown.
SATenstein: Automatically building local search SAT solvers from components.Artificial Intelligence, 232:20–42, 2016.
- Bernd Bischl, Pascal Kerschke, Lars Kotthoff, Marius Thomas Lindauer, Yuri Malitsky, Alexandre Fréchette, Holger H. Hoos, Frank Hutter, Kevin Leyton-Brown, Kevin Tierney and Joaquin Vanschoren.
ASlib: A benchmark library for algorithm selection.Artificial Intelligence, 237:41–58, 2016.
- Chris Fawcett and Holger H. Hoos.
Analysing differences between algorithm configurations through ablation.Journal of Heuristics, 22(4):431–458, 2016.
- Alexandre Fréchette, Lars Kotthoff, Tomasz P. Michalak, Talal Rahwan, Holger H. Hoos and Kevin Leyton-Brown.
Using the Shapley Value to Analyze Algorithm Portfolios.In Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI-16), 3397–3403. AAAI Press, 2016.
- Julieta Martinez, Joris Clement, Holger H. Hoos and James J. Little.
Revisiting Additive Quantization.In Proceedings of the 14th European Conference on Computer Vision (ECCV-16), volume 9906 of Lecture Notes in Computer Science, 137–153. Springer, 2016.
- Julieta Martinez, Holger H. Hoos and James J. Little.
Solving Multi-codebook Quantization in the GPU.In Gang Hua and Hervé Jégou, editors, Proceedings of the ECCV-16 Workshop on Web-scale Vision and Social Media, volume 9913 of Lecture Notes in Computer Science, 638–650. Springer, 2016.
- Holger H. Hoos.
Taming the Complexity Monster or: How I learned to Stop Worrying and Love Hard Problems.In Proceedings of the 2016 on Genetic and Evolutionary Computation Conference, Denver, CO, USA, July 20 - 24, 2016, 3–4. ACM, 2016.
- Sam Bayless, Holger H. Hoos and Alan J. Hu.
Scalable, high-quality, SAT-based multi-layer escape routing.In Proceedings of the 35th International Conference on Computer-Aided Design (ICCAD-16), 22. ACM, 2016.
- Chris Cameron, Holger H. Hoos and Kevin Leyton-Brown.
Bias in Algorithm Portfolio Performance Evaluation.In Proceedings of the 25th International Joint Conference on Artificial Intelligence (IJCAI-15), 712–719. IJCAI/AAAI Press, 2016.
- Aymeric Blot, Holger H. Hoos, Laetitia Jourdan, Marie-Éléonore Kessaci-Marmion and Heike Trautmann.
MO-ParamILS: A Multi-objective Automatic Algorithm Configuration Framework.In Proceedings of the 10th International Conference on Learning and Intelligent Optimization (LION 10), volume 10079 of Lecture Notes in Computer Science, 32–47. Springer, 2016.
- Zongxu Mu, Holger H. Hoos and Thomas Stützle.
The Impact of Automated Algorithm Configuration on the Scaling Behaviour of State-of-the-Art Inexact TSP Solvers.In Proceedings of the 10th International Conference on Learning and Intelligent Optimization (LION 10), volume 10079 of Lecture Notes in Computer Science, 157–172. Springer, 2016.
- Lin Xu, Ashiqur R. KhudaBukhsh, Holger H. Hoos and Kevin Leyton-Brown.
Quantifying the Similarity of Algorithm Configurations.In Proceedings of the 10th International Conference on Learning and Intelligent Optimization (LION 10), volume 10079 of Lecture Notes in Computer Science, 203–217. Springer, 2016.
- Holger H. Hoos, Frank Neumann and Heike Trautmann.
Automated Algorithm Selection and Configuration (Dagstuhl Seminar 16412).Dagstuhl Reports, 6(10):33–74, 2016.
- Mitra Baratchi, Lennart Teunissen, Peter Ebben, Wouter Teeuw, Jan Laarhuis and Maarten van Steen.
Towards Decisive Garments for Heat Stress Risk Detection.In Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct, 1095–1100. 2016.
- Mozhdeh Gholibeigi, Mitra Baratchi, Hans van den Berg and Geert Heijenk.
Towards Reliable Multi-hop Broadcast in VANETs: An Analytical Approach.In 2016 IEEE Vehicular Networking Conference (VNC), 1–8. 2016.
- Bernd Meijerink, Mitra Baratchi and Geert Heijenk.
An Efficient Geographical Addressing Scheme for the Internet.In Wired/Wireless Internet Communications, 78–90. 2016.
- Sarwar Morshed, Mitra Baratchi and Geert Heijenk.
Traffic-adaptive Duty Cycle Adaptation in TR-MAC Protocol for Wireless Sensor Networks.In 2016 Wireless Days (WD), 1–6. 2016.
- Sarwar Morshed, Mitra Baratchi, Pranab. K. Mandal and Geert Heijenk.
A Multi-channel Multiple Access Scheme Using Frequency Offsets-Modelling and analysis.In 2016 IEEE 12th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob), 1–7. 2016.
2015
- Marius Thomas Lindauer, Holger H. Hoos, Frank Hutter and Torsten Schaub.
AutoFolio: An Automatically Configured Algorithm Selector.Journal of Artificial Intelligence Research, 53:745–778, 2015.
- Holger H. Hoos and Thomas Stützle.
On the empirical time complexity of finding optimal solutions vs proving optimality for Euclidean TSP instances.Optimization Letters, 9(6):1247–1254, 2015.
- Holger H. Hoos, Roland Kaminski, Marius Thomas Lindauer and Torsten Schaub.
aspeed: Solver scheduling via answer set programming.TPLP, 15(1):117–142, 2015.
- Katharina Eggensperger, Frank Hutter, Holger H. Hoos and Kevin Leyton-Brown.
Efficient Benchmarking of Hyperparameter Optimizers via Surrogates.In Blai Bonet and Sven Koenig, editors, Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, January 25-30, 2015, Austin, Texas, USA., 1114–1120. AAAI Press, 2015.
- Sam Bayless, Noah Bayless, Holger H. Hoos and Alan J. Hu.
SAT Modulo Monotonic Theories.In Blai Bonet and Sven Koenig, editors, Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, January 25-30, 2015, Austin, Texas, USA., 3702–3709. AAAI Press, 2015.
- Marius Lindauer, Holger H. Hoos, Frank Hutter and Torsten Schaub.
AutoFolio: Algorithm Configuration for Algorithm Selection.In Frank Hutter, Marius Lindauer and Yuri Malitsky, editors, Algorithm Configuration, Papers from the 2015 AAAI Workshop, Austin, Texas, USA, January 26, 2015., volume WS-15-01 of AAAI Workshops. AAAI Press, 2015.
- Jérémie Dubois-Lacoste, Holger H. Hoos and Thomas Stützle.
On the Empirical Scaling Behaviour of State-of-the-art Local Search Algorithms for the Euclidean TSP.In Sara Silva and Anna Isabel Esparcia-Alcázar, editors, Proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2015, Madrid, Spain, July 11-15, 2015, 377–384. ACM, 2015.
- Zongxu Mu and Holger H. Hoos.
Empirical Scaling Analyser: An Automated System for Empirical Analysis of Performance Scaling.In Sara Silva and Anna Isabel Esparcia-Alcázar, editors, Genetic and Evolutionary Computation Conference, GECCO 2015, Madrid, Spain, July 11-15, 2015, Companion Material Proceedings, 771–772. ACM, 2015.
- Mattia Rizzini, Chris Fawcett, Mauro Vallati, Alfonso Emilio Gerevini and Holger H. Hoos.
Portfolio Methods for Optimal Planning: An Empirical Analysis.In 27th IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2015, Vietri sul Mare, Italy, November 9-11, 2015, 494–501. IEEE Computer Society, 2015.
- Zongxu Mu and Holger H. Hoos.
On the Empirical Time Complexity of Random 3-SAT at the Phase Transition.In Qiang Yang and Michael Wooldridge, editors, Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, IJCAI 2015, Buenos Aires, Argentina, July 25-31, 2015, 367–373. AAAI Press, 2015.
- Frank Hutter, Lin Xu, Holger Hoos and Kevin Leyton-Brown.
Algorithm Runtime Prediction: Methods and Evaluation (Extended Abstract).In Qiang Yang and Michael Wooldridge, editors, Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, IJCAI 2015, Buenos Aires, Argentina, July 25-31, 2015, 4197–4201. AAAI Press, 2015.
- Marius Thomas Lindauer, Holger H. Hoos and Frank Hutter.
From Sequential Algorithm Selection to Parallel Portfolio Selection.In Clarisse Dhaenens, Laetitia Jourdan and Marie-Eléonore Marmion, editors, Learning and Intelligent Optimization - 9th International Conference, LION 9, Lille, France, January 12-15, 2015. Revised Selected Papers, volume 8994 of Lecture Notes in Computer Science, 1–16. Springer, 2015.
- Sepp Hartung and Holger H. Hoos.
Programming by Optimisation Meets Parameterised Algorithmics: A Case Study for Cluster Editing.In Clarisse Dhaenens, Laetitia Jourdan and Marie-Eléonore Marmion, editors, Learning and Intelligent Optimization - 9th International Conference, LION 9, Lille, France, January 12-15, 2015. Revised Selected Papers, volume 8994 of Lecture Notes in Computer Science, 43–58. Springer, 2015.
- Lars Kotthoff, Pascal Kerschke, Holger Hoos and Heike Trautmann.
Improving the State of the Art in Inexact TSP Solving Using Per-Instance Algorithm Selection.In Clarisse Dhaenens, Laetitia Jourdan and Marie-Eléonore Marmion, editors, Learning and Intelligent Optimization - 9th International Conference, LION 9, Lille, France, January 12-15, 2015. Revised Selected Papers, volume 8994 of Lecture Notes in Computer Science, 202–217. Springer, 2015.
- Frederick Tung, Julieta Martinez, Holger H. Hoos and James J. Little.
Bank of Quantization Models: A Data-Specific Approach to Learning Binary Codes for Large-Scale Retrieval Applications.In 2015 IEEE Winter Conference on Applications of Computer Vision, WACV 2015, Waikoloa, HI, USA, January 5-9, 2015, 566–571. IEEE Computer Society, 2015.
- Holger H. Hoos and Thomas Stützle.
Stochastic Local Search Algorithms: An Overview.In Janusz Kacprzyk and Witold Pedrycz, editors, Springer Handbook of Computational Intelligence, pages 1085–1105. Springer, 2015.
- Frank Hutter, Marius Thomas Lindauer, Adrian Balint, Sam Bayless, Holger H. Hoos and Kevin Leyton-Brown.
The Configurable SAT Solver Challenge (CSSC).CoRR, 2015.
- Bernd Bischl, Pascal Kerschke, Lars Kotthoff, Marius Thomas Lindauer, Yuri Malitsky, Alexandre Fréchette, Holger H. Hoos, Frank Hutter, Kevin Leyton-Brown, Kevin Tierney and Joaquin Vanschoren.
ASlib: A Benchmark Library for Algorithm Selection.CoRR, 2015.
2014
- Frank Hutter, Lin Xu, Holger H. Hoos and Kevin Leyton-Brown.
Algorithm runtime prediction: Methods & evaluation.Artif. Intell., 206:79–111, 2014.
- Kieran O'Neill, Adrin Jalali, Nima Aghaeepour, Holger Hoos and Ryan R. Brinkman.
Enhanced flowType/RchyOptimyx: a Bioconductor pipeline for discovery in high-dimensional cytometry data.Bioinformatics, 30(9):1329–1330, 2014.
- Kevin Leyton-Brown, Holger H. Hoos, Frank Hutter and Lin Xu.
Understanding the empirical hardness of NP-complete problems.Commun. ACM, 57(5):98–107, 2014.
- Holger H. Hoos and Thomas Stützle.
On the empirical scaling of run-time for finding optimal solutions to the travelling salesman problem.European Journal of Operational Research, 238(1):87–94, 2014.
- Holger Hoos, Marius Thomas Lindauer and Torsten Schaub.
claspfolio 2: Advances in Algorithm Selection for Answer Set Programming.TPLP, 14(4-5):569–585, 2014.
- Lucas Majerowicz, Ariel Shamir, Alla Sheffer and Holger H. Hoos.
Filling Your Shelves: Synthesizing Diverse Style-Preserving Artifact Arrangements.IEEE Trans. Vis. Comput. Graph., 20(11):1507–1518, 2014.
- Chris Fawcett, Mauro Vallati, Frank Hutter, Jörg Hoffmann, Holger H. Hoos and Kevin Leyton-Brown.
Improved Features for Runtime Prediction of Domain-Independent Planners.In Steve A. Chien, Minh Binh Do, Alan Fern and Wheeler Ruml, editors, Proceedings of the Twenty-Fourth International Conference on Automated Planning and Scheduling, ICAPS 2014, Portsmouth, New Hampshire, USA, June 21-26, 2014. AAAI, 2014.
- Katharina Eggensperger, Frank Hutter, Holger H. Hoos and Kevin Leyton-Brown.
Surrogate Benchmarks for Hyperparameter Optimization.In Joaquin Vanschoren, Pavel Brazdil, Carlos Soares and Lars Kotthoff, editors, 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., volume 1201 of CEUR Workshop Proceedings, 24–31. CEUR-WS.org, 2014.
- Frank Hutter, Holger Hoos and Kevin Leyton-Brown.
An Efficient Approach for Assessing Hyperparameter Importance.In Proceedings of the 31th International Conference on Machine Learning, ICML 2014, Beijing, China, 21-26 June 2014, volume 32 of JMLR Workshop and Conference Proceedings, 754–762. JMLR.org, 2014.
- Frank Hutter, Manuel López-Ibá~nez, Chris Fawcett, Marius Thomas Lindauer, Holger H. Hoos, Kevin Leyton-Brown and Thomas Stützle.
AClib: A Benchmark Library for Algorithm Configuration.In Panos M. Pardalos, Mauricio G. C. Resende, Chrysafis Vogiatzis and Jose L. Walteros, editors, Learning and Intelligent Optimization - 8th International Conference, Lion 8, Gainesville, FL, USA, February 16-21, 2014. Revised Selected Papers, volume 8426 of Lecture Notes in Computer Science, 36–40. Springer, 2014.
- Daniel Geschwender, Frank Hutter, Lars Kotthoff, Yuri Malitsky, Holger H. Hoos, Kevin Leyton-Brown, D. Geschwender, F. Hutter, L. Kotthoff, Y. Malitsky, H. H. Hoos and K. Leyton-Brown.
Algorithm Configuration in the Cloud: A Feasibility Study.In Panos M. Pardalos, Mauricio G. C. Resende, Chrysafis Vogiatzis and Jose L. Walteros, editors, Learning and Intelligent Optimization - 8th International Conference, Lion 8, Gainesville, FL, USA, February 16-21, 2014. Revised Selected Papers, volume 8426 of Lecture Notes in Computer Science, 41–46. Springer, 2014.
- Sam Bayless, Dave A. D. Tompkins and Holger H. Hoos.
Evaluating Instance Generators by Configuration.In Panos M. Pardalos, Mauricio G. C. Resende, Chrysafis Vogiatzis and Jose L. Walteros, editors, Learning and Intelligent Optimization - 8th International Conference, Lion 8, Gainesville, FL, USA, February 16-21, 2014. Revised Selected Papers, volume 8426 of Lecture Notes in Computer Science, 47–61. Springer, 2014.
- Holger Hoos, Roland Kaminski, Marius Thomas Lindauer and Torsten Schaub.
Solver Scheduling via Answer Set Programming.CoRR, 2014.
- Holger Hoos, Marius Thomas Lindauer and Torsten Schaub.
claspfolio 2: Advances in Algorithm Selection for Answer Set Programming.CoRR, 2014.
- Sam Bayless, Noah Bayless, Holger H. Hoos and Alan J. Hu.
SAT Modulo Monotonic Theories.CoRR, 2014.
- Julieta Martinez, Holger H. Hoos and James J. Little.
Stacked Quantizers for Compositional Vector Compression.CoRR, 2014.
- Mitra Baratchi, Nirvana Meratnia, Paul J. M. Havinga, Andrew K. Skidmore and Bert A. K. G. Toxopeus.
A Hierarchical Hidden semi-Markov Model for Modeling Mobility Data.In Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing, 401–412. 2014.
- Mitra Baratchi, Nirvana Meratnia and Paul J. M. Havinga.
Recognition of Periodic Behavioral Patterns from Streaming Mobility Data.In Mobile and Ubiquitous Systems: Computing, Networking, and Services, 102–115. 2014.
2013
- Nima Aghaeepour and Holger H. Hoos.
Ensemble-based prediction of RNA secondary structures.BMC Bioinformatics, 14:139, 2013.
- Sam Bayless, Celina G. Val, Thomas Ball, Holger H. Hoos and Alan J. Hu.
Efficient modular SAT solving for IC3.In Formal Methods in Computer-Aided Design, FMCAD 2013, Portland, OR, USA, October 20-23, 2013, 149–156. IEEE, 2013.
- James Styles and Holger Hoos.
Ordered racing protocols for automatically configuring algorithms for scaling performance.In Christian Blum and Enrique Alba, editors, Genetic and Evolutionary Computation Conference, GECCO '13, Amsterdam, The Netherlands, July 6-10, 2013, 551–558. ACM, 2013.
- Frank Hutter, Holger Hoos and Kevin Leyton-Brown.
An evaluation of sequential model-based optimization for expensive blackbox functions.In Christian Blum and Enrique Alba, editors, Genetic and Evolutionary Computation Conference, GECCO '13, Amsterdam, The Netherlands, July 6-10, 2013, Companion Material Proceedings, 1209–1216. ACM, 2013.
- Katharina Eggensperger, Matthias Feurer, Frank Hutter, James Bergstra, Jasper Snoek, Holger Hoos and Kevin Leyton-Brown.
Towards an Empirical Foundation for Assessing Bayesian Optimization of Hyperparameters.In NIPS workshop on Bayesian Optimization in Theory and Practice. dec 2013.
- Chris Thornton, Frank Hutter, Holger H. Hoos and Kevin Leyton-Brown.
Auto-WEKA: combined selection and hyperparameter optimization of classification algorithms.In Inderjit S. Dhillon, Yehuda Koren, Rayid Ghani, Ted E. Senator, Paul Bradley, Rajesh Parekh, Jingrui He, Robert L. Grossman and Ramasamy Uthurusamy, editors, The 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2013, Chicago, IL, USA, August 11-14, 2013, 847–855. ACM, 2013.
- Holger H. Hoos, Benjamin Kaufmann, Torsten Schaub and Marius Schneider.
Robust Benchmark Set Selection for Boolean Constraint Solvers.In Giuseppe Nicosia and Panos M. Pardalos, editors, Learning and Intelligent Optimization - 7th International Conference, LION 7, Catania, Italy, January 7-11, 2013, Revised Selected Papers, volume 7997 of Lecture Notes in Computer Science, 138–152. Springer, 2013.
- Frank Hutter, Holger H. Hoos and Kevin Leyton-Brown.
Identifying Key Algorithm Parameters and Instance Features Using Forward Selection.In Giuseppe Nicosia and Panos M. Pardalos, editors, Learning and Intelligent Optimization - 7th International Conference, LION 7, Catania, Italy, January 7-11, 2013, Revised Selected Papers, volume 7997 of Lecture Notes in Computer Science, 364–381. Springer, 2013.
- James Styles and Holger H. Hoos.
Using Racing to Automatically Configure Algorithms for Scaling Performance.In Giuseppe Nicosia and Panos M. Pardalos, editors, Learning and Intelligent Optimization - 7th International Conference, LION 7, Catania, Italy, January 7-11, 2013, Revised Selected Papers, volume 7997 of Lecture Notes in Computer Science, 382–388. Springer, 2013.
- Mauro Vallati, Chris Fawcett, Alfonso Gerevini, Holger H. Hoos and Alessandro Saetti.
Automatic Generation of Efficient Domain-Optimized Planners from Generic Parametrized Planners.In Malte Helmert and Gabriele Röger, editors, Proceedings of the Sixth Annual Symposium on Combinatorial Search, SOCS 2013, Leavenworth, Washington, USA, July 11-13, 2013. AAAI Press, 2013.
- Craig Boutilier, Ronen I. Brafman, Holger H. Hoos and David Poole.
Reasoning With Conditional Ceteris Paribus Preference Statem.CoRR, 2013.
- Holger H. Hoos and Thomas Stützle.
Evaluating Las Vegas Algorithms - Pitfalls and Remedies.CoRR, 2013.
- Frank Hutter, Holger Hoos and Kevin Leyton-Brown.
Bayesian Optimization With Censored Response Data.CoRR, 2013.
- Nima Aghaeepour, Greg Finak, Holger Hoos, Tim R Mosmann, Ryan Brinkman, Raphael Gottardo, Richard H Scheuermann, FlowCAP Consortium, DREAM Consortium and others.
Critical assessment of automated flow cytometry data analysis techniques.Nature methods, 10(3):228–238, 2013.
- Siavash Aflaki, Nirvana Meratnia, Mitra Baratchi and Paul J. M. Havinga.
Evaluation of Incentives for Body Area Network-based Healthcare Systems.In 2013 IEEE Eighth International Conference on Intelligent Sensors, Sensor Networks and Information Processing, 515–520. 2013.
- Mitra Baratchi, Nirvana Meratnia, Paul J. M. Havinga, Andrew K. Skidmore and Bert A. G. Toxopeus.
Sensing Solutions for Collecting Spatio-Temporal Data for Wildlife Monitoring Applications: A Review.Sensors, 13(5):6054–6088, 2013.
- Mitra Baratchi, Nirvana Meratnia and Paul J. M. Havinga.
Finding Frequently Visited Paths: Dealing with the Uncertainty of Spatio-temporal Mobility Data.In 2013 IEEE Eighth International Conference on Intelligent Sensors, Sensor Networks and Information Processing, 479–484. 2013.
- Mitra Baratchi, Nirvana Meratnia and Paul J. M. Havinga.
On the Use of Mobility Data for Discovery and Description of Social Ties.In Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, 1229–1236. 2013.
2012
- Nima Aghaeepour, Pratip K. Chattopadhyay, Anuradha Ganesan, Kieran O'Neill, Habil Zare, Adrin Jalali, Holger H. Hoos, Mario Roederer and Ryan R. Brinkman.
Early immunologic correlates of HIV protection can be identified from computational analysis of complex multivariate T-cell flow cytometry assays.Bioinformatics, 28(7):1009–1016, 2012.
- Monir Hajiaghayi, Anne Condon and Holger H. Hoos.
Analysis of energy-based algorithms for RNA secondary structure prediction.BMC Bioinformatics, 13:22, 2012.
- Holger H. Hoos.
Programming by optimization.Commun. ACM, 55(2):70–80, 2012.
- Lin Xu, Holger H. Hoos and Kevin Leyton-Brown.
Predicting Satisfiability at the Phase Transition.In Jörg Hoffmann and Bart Selman, editors, Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence, July 22-26, 2012, Toronto, Ontario, Canada. AAAI Press, 2012.
- Holger Hoos, Roland Kaminski, Torsten Schaub and Marius Thomas Schneider.
aspeed: ASP-based Solver Scheduling.In Agostino Dovier and V\'ıtor Santos Costa, editors, Technical Communications of the 28th International Conference on Logic Programming, ICLP 2012, September 4-8, 2012, Budapest, Hungary, volume 17 of LIPIcs, 176–187. Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik, 2012.
- Frank Hutter, Holger H. Hoos and Kevin Leyton-Brown.
Parallel Algorithm Configuration.In Youssef Hamadi and Marc Schoenauer, editors, Learning and Intelligent Optimization - 6th International Conference, LION 6, Paris, France, January 16-20, 2012, Revised Selected Papers, volume 7219 of Lecture Notes in Computer Science, 55–70. Springer, 2012.
- Marius Schneider and Holger H. Hoos.
Quantifying Homogeneity of Instance Sets for Algorithm Configuration.In Youssef Hamadi and Marc Schoenauer, editors, Learning and Intelligent Optimization - 6th International Conference, LION 6, Paris, France, January 16-20, 2012, Revised Selected Papers, volume 7219 of Lecture Notes in Computer Science, 190–204. Springer, 2012.
- James Styles, Holger H. Hoos and Martin Müller.
Automatically Configuring Algorithms for Scaling Performance.In Youssef Hamadi and Marc Schoenauer, editors, Learning and Intelligent Optimization - 6th International Conference, LION 6, Paris, France, January 16-20, 2012, Revised Selected Papers, volume 7219 of Lecture Notes in Computer Science, 205–219. Springer, 2012.
- Lin Xu, Frank Hutter, Holger Hoos and Kevin Leyton-Brown.
Evaluating Component Solver Contributions to Portfolio-Based Algorithm Selectors.In Alessandro Cimatti and Roberto Sebastiani, editors, Theory and Applications of Satisfiability Testing - SAT 2012 - 15th International Conference, Trento, Italy, June 17-20, 2012. Proceedings, volume 7317 of Lecture Notes in Computer Science, 228–241. Springer, 2012.
- Holger H. Hoos.
Automated Algorithm Configuration and Parameter Tuning.In Youssef Hamadi, Eric Monfroy and Frédéric Saubion, editors, Autonomous Search, pages 37–71. Springer, 2012.
- Chris Thornton, Frank Hutter, Holger H. Hoos and Kevin Leyton-Brown.
Auto-WEKA: Automated Selection and Hyper-Parameter Optimization of Classification Algorithms.CoRR, 2012.
- Frank Hutter, Lin Xu, Holger H. Hoos and Kevin Leyton-Brown.
Algorithm Runtime Prediction: The State of the Art.CoRR, 2012.
- Holger H. Hoos, Kevin Leyton-Brown, Torsten Schaub and Marius Schneider.
Algorithm Configuration for Portfolio-based Parallel SAT-Solving.In Proceedings of the ECAI-12 Workshop on Combining Constraint Solving with MIning and Learning. 2012. (6 pages).
- Nima Aghaeepour, Adrin Jalali, Kieran O'Neill, Pratip K. Chattopadhyay, Mario Roederer, Holger H. Hoos and Ryan R. Brinkman.
RchyOptimyx: Cellular hierarchy optimization for flow cytometry.Cytometry Part A, 81A(12):1022–1030, 2012.
2011
- Dave A. D. Tompkins, Adrian Balint and Holger H. Hoos.
Captain Jack: New Variable Selection Heuristics in Local Search for SAT.In Proceedings of the 14th International Conference on Theory and Applications of Satisfiability Testing (SAT 2011), 302–316. 2011.
- Mauro Vallati, Chris Fawcett, Alfonso Gerevini, Holger H. Hoos and Alessandro Saetti.
Automatic Generation of Efficient Domain-Optimized Planners from Generic Parametrized Planners.In Proceedings of the 18th RCRA Workshop on Experimental Evaluation of Algorithms for Solving Problems with Combinatorial Explosion (RCRA 2011), 111–123. 2011.
- Lin Xu, Frank Hutter, Holger H. Hoos and Kevin Leyton-Brown.
Hydra-MIP: Automated Algorithm Configuration and Selection for Mixed Integer Programming.In Proceedings of the 18th RCRA Workshop on Experimental Evaluation of Algorithms for Solving Problems with Combinatorial Explosion (RCRA 2011), 16–30. 2011.
- Chris Fawcett, Malte Helmert, Holger Hoos, Erez Karpas, Gabriele Röger and Jendrik Seipp.
FD-Autotune: Domain-Specific Configuration using Fast Downward.In Proceedings of the ICAPS Workshop on Planning and Learning (PAL 2011), 13–20. 2011.
- Christopher Nell, Chris Fawcett, Holger H. Hoos and Kevin Leyton-Brown.
HAL: A Framework for the Automated Design and Analysis of High-Performance Algorithms.In Proceedings of the 5th International Conference on Learning and Intelligent Optimization (LION 5), 600–615. 2011.
- Frank Hutter, Holger H. Hoos and Kevin Leyton-Brown.
Sequential Model-Based Optimization for General Algorithm Configuration.In Proceedings of the 5th International Conference on Learning and Intelligent Optimization (LION 5), 507–523. 2011.
- Nima Aghaeepour, Radina Nikolic, Holger H. Hoos and Ryan R. Brinkman.
Rapid cell population identification in flow cytometry data.Cytometry Part A, 79A(1):6–13, 2011.
- Therese Biedl, Stephane Durocher, Holger H. Hoos, Shuang Luan, Jared Saia and Maxwell Young.
A Note on Improving the Performance of Approximation Algorithms for Radiation Therapy.Information Processing Letters, 111(7):326–333, 2011.
2010
- Frank Hutter, Holger H. Hoos and Kevin Leyton-Brown.
Tradeoffs in the empirical evaluation of competing algorithm designs.Annals of Mathematics and Artificial Intelligence, 60(1-2):65–89, 2010.
- Mirela Andronescu, Anne Condon, Holger H. Hoos, David H. Mathews and Kevin P. Murphy.
Computational approaches for RNA energy parameter estimation.RNA, 16(12):2304–2318, 2010.
- Lin Xu, Holger H. Hoos and Kevin Leyton-Brown.
Hydra: Automatically Configuring Algorithms for Portfolio-Based Selection.In Proceedings of the 24th AAAI Conference on Artificial Intelligence (AAAI 2010), 210–216. 2010.
- Dave A.D. Tompkins and Holger H. Hoos.
Dynamic Scoring Functions with Variable Expressions: New SLS Methods for Solving SAT.In Proceedings of the 13th International Conference on Theory and Applications of Satisfiability Testing (SAT 2010), 278–292. 2010.
- Frank Hutter, Holger H. Hoos and Kevin Leyton-Brown.
Automated Configuration of Mixed Integer Programming Solvers.In Proceedings of the 7th International Conference on the Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems (CPAIOR 2010), 186–202. 2010.
- Frank Hutter, Thomas Bartz-Beielstein, Holger H. Hoos, Kevin Leyton-Brown and Kevin P. Murphy.
Sequential Model-Based Parameter Optimisation: An Experimental Investigation of Automated and interactive Approaches.In T. Bartz-Beielstein, M. Chiarandini, L. Paquete and M. Preuss, editors, Empirical Methods for the Analysis of Optimization Algorithms, chapter 15, pages 363–414. Springer-Verlag, Berlin/Heidelberg, Germany, 2010.
- Frank Hutter, Holger H. Hoos, Kevin Leyton-Brown and Kevin Murphy.
Time-Bounded Sequential Parameter Optimization.In Proceedings of the 4th International Conference on Learning and Intelligent Optimization (LION 4), 281–298. 2010.
2009
- Frank Hutter, Holger H. Hoos, Kevin Leyton-Brown and Thomas Stützle.
ParamILS: An Automatic Algorithm Configuration Framework.Journal of Artificial Intelligence Research, 36:267–306, 2009.
- Ashiqur R. KhudaBukhsh, Lin Xu, Holger H. Hoos and Kevin Leyton-Brown.
SATenstein: Automatically Building Local Search SAT Solvers From Components.In Proceedings of the 21st International Joint Conference on Artificial Intelligence (IJCAI 2009), 517–524. 2009.
- Frank Hutter, Holger H. Hoos, Kevin Leyton-Brown and Kevin Murphy.
An Experimental Investigation of Model-Based Parameter Optimisation: SPO and Beyond.In Proceedings of the 11th Annual Conference on Genetic and Evolutionary Computation (GECCO 2009), 271–278. 2009.
2008
- Holger H. Hoos.
Computer-Aided Design of High-Performance Algorithms.Technical Report TR-2008-16, Department of Computer Science, University of British Columbia, December 2008.
- Marco Chiarandini, Chris Fawcett and Holger H. Hoos.
A Modular Multiphase Heuristic Solver for Post Enrollment Course Timetabling (Extended Abstract).In Proceedings of the 7th International Conference on the Practice and Theory of Automated Timetabling (PATAT 2008). 2008.
- Mirela Andronescu, Vera Bereg, Holger H. Hoos and Anne Condon.
RNA STRAND: The RNA Secondary Structure and Statistical Analysis Database.BMC Bioinformatics, 9:340, 2008.
- Sanja Rogic, Ben Montpetit, Holger H. Hoos, Alan K. Mackworth, B.F. Francis Ouellette and Philip Hieter.
Correlation between the secondary structure of pre-mRNA and efficiency of splicing in Saccharomyces cerevisiae.BMC Genomics, 9:355, 2008.
- Lin Xu, Frank Hutter, Holger H. Hoos and Kevin Leyton-Brown.
SATzilla: Portfolio-based Algorithm Selection for SAT.Journal of Artificial Intelligence Research, 32:565–606, 2008. This paper won the 2010 IJCAI-JAIR Best Paper Prize, and the portfolio-based SAT solvers described in it won 3 gold medals, 1 silver and 1 bronze in the 2007 SAT competition. This article is a significantly expanded version of our earlier CP-07 paper with improved methodology and algorithms. The same methodology underlies a later version of SATzilla, which won 3 gold and 2 silver medals in the 2009 SAT competition.
- Mauro Brunato, Holger H. Hoos and Roberto Battiti.
On Effectively Finding Maximal Quasi-Cliques in Graphs.In Proceedings of the 2nd Learning and Intelligent Optimization Conference (LION 2), 41–55. 2008.
Before 2008
For earlier publications, please see Holger's Google Scholar profile or UBC publication page.