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ORCIDHolger H. Hoos
Person information
- affiliation: RWTH Aachen University, Computer Science Department, Aachen, Germany
- affiliation: Leiden University, LIACS, The Netherlands
- affiliation: University of British Columbia, Vancouver, BC, Canada
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2020 – today
- 2024
[j80]Julian Dierkes, Emma Cramer, Holger H. Hoos, Sebastian Trimpe:
Combining Automated Optimisation of Hyperparameters and Reward Shape. RLJ 3: 1441-1466 (2024)- [j79]Bram M. Renting, Thomas M. Moerland, Holger H. Hoos, Catholijn M. Jonker:
Towards General Negotiation Strategies with End-to-End Reinforcement Learning. RLJ 5: 2059-2070 (2024) - [j78]Mitra Baratchi, Can Wang, Steffen Limmer, Jan N. van Rijn, Holger H. Hoos, Thomas Bäck, Markus Olhofer:
Automated machine learning: past, present and future. Artif. Intell. Rev. 57(5): 122 (2024) - [j77]Matthias König, Annelot W. Bosman, Holger H. Hoos, Jan N. van Rijn:
Critically Assessing the State of the Art in Neural Network Verification. J. Mach. Learn. Res. 25: 12:1-12:53 (2024) - [j76]Alex Serban, Koen van der Blom
, Holger H. Hoos, Joost Visser:
Software engineering practices for machine learning - Adoption, effects, and team assessment. J. Syst. Softw. 209: 111907 (2024) - [j75]Julia Wasala, Suzanne M. Marselis, Laurens Arp, Holger H. Hoos, Nicolas Longépé, Mitra Baratchi:
AutoSR4EO: An AutoML Approach to Super-Resolution for Earth Observation Images. Remote. Sens. 16(3): 443 (2024) - [c142]Matthias König, Holger H. Hoos, Jan N. van Rijn:
Accelerating Adversarially Robust Model Selection for Deep Neural Networks via Racing. AAAI 2024: 21267-21275 - [c141]Jeroen Rook, Holger H. Hoos, Heike Trautmann:
Multi-objective Ranking using Bootstrap Resampling. GECCO Companion 2024: 155-158 - [c140]Matthias König, Xiyue Zhang, Holger H. Hoos, Marta Kwiatkowska, Jan N. van Rijn:
Automated Design of Linear Bounding Functions for Sigmoidal Nonlinearities in Neural Networks. ECML/PKDD (7) 2024: 383-398 - [c139]Annelot W. Bosman, Anna L. Münz, Holger H. Hoos, Jan N. van Rijn:
A Preliminary Study to Examining Per-class Performance Bias via Robustness Distributions. SAIV 2024: 116-133 - [c138]Hadar Shavit, Holger H. Hoos:
Revisiting SATZilla Features in 2024. SAT 2024: 27:1-27:26 - [i38]Matthias König, Xiyue Zhang, Holger H. Hoos, Marta Kwiatkowska, Jan N. van Rijn:
Automated Design of Linear Bounding Functions for Sigmoidal Nonlinearities in Neural Networks. CoRR abs/2406.10154 (2024) - [i37]Bram M. Renting, Thomas M. Moerland, Holger H. Hoos, Catholijn M. Jonker:
Towards General Negotiation Strategies with End-to-End Reinforcement Learning. CoRR abs/2406.15096 (2024) - [i36]Julian Dierkes, Emma Cramer, Holger H. Hoos, Sebastian Trimpe:
Combining Automated Optimisation of Hyperparameters and Reward Shape. CoRR abs/2406.18293 (2024) - [i35]Thijs Snelleman, Bram M. Renting, Holger H. Hoos, Jan N. van Rijn:
Edge-Based Graph Component Pooling. CoRR abs/2409.11856 (2024) - [i34]Jannis Becktepe, Julian Dierkes, Carolin Benjamins, Aditya Mohan, David Salinas, Raghu Rajan, Frank Hutter, Holger H. Hoos, Marius Lindauer, Theresa Eimer:
ARLBench: Flexible and Efficient Benchmarking for Hyperparameter Optimization in Reinforcement Learning. CoRR abs/2409.18827 (2024) - 2023
- [j74]Zhou Zhou, Mitra Baratchi, Gangquan Si, Holger H. Hoos, Gang Huang:
Adaptive error bounded piecewise linear approximation for time-series representation. Eng. Appl. Artif. Intell. 126: 106892 (2023) - [j73]Yi Chu, Chuan Luo, Holger H. Hoos, Haihang You:
Improving the performance of stochastic local search for maximum vertex weight clique problem using programming by optimization. Expert Syst. Appl. 213(Part): 118913 (2023) - [j72]Kevin Baum, Joanna Bryson, Frank Dignum, Virginia Dignum, Marko Grobelnik, Holger H. Hoos, Morten Irgens, Paul Lukowicz, Catelijne Muller, Francesca Rossi, John Shawe-Taylor, Andreas Theodorou, Ricardo Vinuesa:
From fear to action: AI governance and opportunities for all. Frontiers Comput. Sci. 5 (2023) - [c137]Matthias König, Annelot W. Bosman, Holger H. Hoos, Jan N. van Rijn:
Critically Assessing the State of the Art in CPU-based Local Robustness Verification. SafeAI@AAAI 2023 - [c136]Lennart Oswald Purucker, Lennart Schneider, Marie Anastacio, Joeran Beel, Bernd Bischl, Holger H. Hoos:
Q(D)O-ES: Population-based Quality (Diversity) Optimisation for Post Hoc Ensemble Selection in AutoML. AutoML 2023: 10/1-34 - [i33]Devis Tuia, Konrad Schindler, Begüm Demir, Gustau Camps-Valls, Xiao Xiang Zhu, Mrinalini Kochupillai, Saso Dzeroski, Jan N. van Rijn, Holger H. Hoos, Fabio Del Frate, Mihai Datcu, Jorge-Arnulfo Quiané-Ruiz, Volker Markl, Bertrand Le Saux, Rochelle Schneider:
Artificial intelligence to advance Earth observation: a perspective. CoRR abs/2305.08413 (2023) - [i32]Lennart Purucker, Lennart Schneider, Marie Anastacio, Joeran Beel, Bernd Bischl, Holger H. Hoos:
Q(D)O-ES: Population-based Quality (Diversity) Optimisation for Post Hoc Ensemble Selection in AutoML. CoRR abs/2307.08364 (2023) - [i31]Chris Fawcett, Mauro Vallati, Holger H. Hoos, Alfonso Emilio Gerevini:
Competitions in AI - Robustly Ranking Solvers Using Statistical Resampling. CoRR abs/2308.05062 (2023) - [i30]Saso Dzeroski, Holger H. Hoos, Bertrand Le Saux, Leendert van der Torre, Ana Kostovska:
Space and Artificial Intelligence (Dagstuhl Seminar 23461). Dagstuhl Reports 13(11): 72-102 (2023) - 2022
- [j71]Jaco Tetteroo, Mitra Baratchi, Holger H. Hoos:
Automated Machine Learning for COVID-19 Forecasting. IEEE Access 10: 94718-94737 (2022) - [j70]Anna L. D. Latour, Behrouz Babaki, Daniël Fokkinga, Marie Anastacio, Holger H. Hoos, Siegfried Nijssen:
Exact stochastic constraint optimisation with applications in network analysis. Artif. Intell. 304: 103650 (2022) - [j69]Tijl De Bie, Luc De Raedt, José Hernández-Orallo, Holger H. Hoos, Padhraic Smyth, Christopher K. I. Williams:
Automating data science. Commun. ACM 65(3): 76-87 (2022) - [j68]Laurens Arp, Mitra Baratchi, Holger H. Hoos:
VPint: value propagation-based spatial interpolation. Data Min. Knowl. Discov. 36(5): 1647-1678 (2022) - [j67]Holger H. Hoos, Laetitia Jourdan, Marie-Eléonore Kessaci, Thomas Stützle, Nadarajen Veerapen:
Preface to the Special Cluster on Stochastic Local Search: Recent Developments and Trends. Int. Trans. Oper. Res. 29(5): 2735-2736 (2022) - [j66]Matthias König, Holger H. Hoos, Jan N. van Rijn:
Speeding up neural network robustness verification via algorithm configuration and an optimised mixed integer linear programming solver portfolio. Mach. Learn. 111(12): 4565-4584 (2022) - [j65]Koen van der Blom, Holger H. Hoos, Chuan Luo, Jeroen G. Rook:
Sparkle: Toward Accessible Meta-Algorithmics for Improving the State of the Art in Solving Challenging Problems. IEEE Trans. Evol. Comput. 26(6): 1351-1364 (2022) - [j64]Yasha Pushak, Holger H. Hoos:
AutoML Loss Landscapes. ACM Trans. Evol. Learn. Optim. 2(3): 10:1-10:30 (2022) - [c135]Reyhan Aydogan, Tim Baarslag, Katsuhide Fujita, Holger H. Hoos, Catholijn M. Jonker, Yasser Mohammad, Bram M. Renting:
The 13th International Automated Negotiating Agent Competition Challenges and Results. ACAN@IJCAI 2022: 87-101 - [c134]Bram M. Renting, Holger H. Hoos, Catholijn M. Jonker:
Automated Configuration and Usage of Strategy Portfolios Mixed-Motive Bargaining. AAMAS 2022: 1101-1109 - [c133]Damir Pulatov, Marie Anastacio, Lars Kotthoff, Holger H. Hoos:
Opening the Black Box: Automated Software Analysis for Algorithm Selection. AutoML 2022: 6/1-18 - [c132]Marie Anastacio, Théo Matricon, Holger H. Hoos:
Challenges of Acquiring Compositional Inductive Biases via Meta-Learning. Meta-Knowledge Transfer @ ECML/PKDD 2022: 11-23 - [i29]Bram M. Renting, Holger H. Hoos, Catholijn M. Jonker:
Automated Configuration and Usage of Strategy Portfolios for Bargaining. CoRR abs/2212.10228 (2022) - 2021
- [j63]Gilles Ottervanger, Mitra Baratchi, Holger H. Hoos:
MultiETSC: automated machine learning for early time series classification. Data Min. Knowl. Discov. 35(6): 2602-2654 (2021) - [j62]Gianluca Bontempi, Ricardo Chavarriaga, Hans ed Canck, Emanuela Girardi, Holger H. Hoos, Iarla Kilbane-Dawe, Tonio Ball, Ann Nowé, Jose Sousa, Davide Bacciu, Marco Aldinucci, Manlio ed Domenico, Alessandro Saffiotti, Marco Maratea:
The CLAIRE COVID-19 initiative: approach, experiences and recommendations. Ethics Inf. Technol. 23(S1): 127-133 (2021) - [c131]Théo Matricon, Marie Anastacio, Nathanaël Fijalkow, Laurent Simon, Holger H. Hoos:
Statistical Comparison of Algorithm Performance Through Instance Selection. CP 2021: 43:1-43:21 - [c130]Alex Serban, Koen van der Blom, Holger H. Hoos, Joost Visser:
Practices for Engineering Trustworthy Machine Learning Applications. WAIN@ICSE 2021: 97-100 - [c129]Bruno Veloso, Luciano Caroprese, Matthias König, Sónia Teixeira, Giuseppe Manco, Holger H. Hoos, João Gama:
Hyper-parameter Optimization for Latent Spaces. ECML/PKDD (3) 2021: 249-264 - [c128]Zhendong Lei, Shaowei Cai, Chuan Luo, Holger H. Hoos:
Efficient Local Search for Pseudo Boolean Optimization. SAT 2021: 332-348 - [p9]Holger H. Hoos, Frank Hutter, Kevin Leyton-Brown:
Automated Configuration and Selection of SAT Solvers. Handbook of Satisfiability 2021: 481-507 - [p8]Andreas Dengel, Oren Etzioni, Nicole DeCario, Holger H. Hoos, Li Fei-Fei, Junichi Tsujii, Paolo Traverso:
Next Big Challenges in Core AI Technology. Reflections on Artificial Intelligence for Humanity 2021: 90-115 - [i28]Alex Serban, Koen van der Blom, Holger H. Hoos, Joost Visser:
Practices for Engineering Trustworthy Machine Learning Applications. CoRR abs/2103.00964 (2021) - [i27]Tijl De Bie, Luc De Raedt, José Hernández-Orallo, Holger H. Hoos, Padhraic Smyth, Christopher K. I. Williams:
Automating Data Science: Prospects and Challenges. CoRR abs/2105.05699 (2021) - [i26]Mikhail Evchenko, Joaquin Vanschoren, Holger H. Hoos, Marc Schoenauer, Michèle Sebag:
Frugal Machine Learning. CoRR abs/2111.03731 (2021) - 2020
- [j61]Sam Bayless, Nodir Kodirov, Syed M. Iqbal, Ivan Beschastnikh, Holger H. Hoos, Alan J. Hu:
Scalable constraint-based virtual data center allocation. Artif. Intell. 278 (2020) - [j60]Yasha Pushak, Zongxu Mu, Holger H. Hoos:
Empirical scaling analyzer: An automated system for empirical analysis of performance scaling. AI Commun. 33(2): 93-111 (2020) - [j59]Zeynep Akata, Dan Balliet, Maarten de Rijke, Frank Dignum, Virginia Dignum, Guszti Eiben, Antske Fokkens, Davide Grossi, Koen V. Hindriks, Holger H. Hoos, Hayley Hung, Catholijn M. Jonker, Christof Monz, Mark A. Neerincx, Frans A. Oliehoek, Henry Prakken, Stefan Schlobach, Linda C. van der Gaag, Frank van Harmelen, Herke van Hoof, Birna van Riemsdijk, Aimee van Wynsberghe, Rineke Verbrugge, Bart Verheij, Piek Vossen, Max Welling:
A Research Agenda for Hybrid Intelligence: Augmenting Human Intellect With Collaborative, Adaptive, Responsible, and Explainable Artificial Intelligence. Computer 53(8): 18-28 (2020) - [j58]Holger H. Hoos, Laetitia Jourdan, Marie-Eléonore Kessaci, Thomas Stützle, Nadarajen Veerapen:
Special issue on "Stochastic Local Search: Recent developments and trends". Int. Trans. Oper. Res. 27(1): 697-698 (2020) - [j57]Holger H. Hoos, Laetitia Jourdan, Marie-Eléonore Kessaci, Thomas Stützle, Nadarajen Veerapen:
Special issue on "Stochastic Local Search: Recent developments and trends". Int. Trans. Oper. Res. 27(2): 1263-1264 (2020) - [j56]Holger H. Hoos, Laetitia Jourdan, Marie-Eléonore Kessaci, Thomas Stützle, Nadarajen Veerapen:
Special issue on "Stochastic Local Search: Recent developments and trends". Int. Trans. Oper. Res. 27(3): 1806-1807 (2020) - [j55]Holger H. Hoos, Laetitia Jourdan, Marie-Eléonore Kessaci, Thomas Stützle, Nadarajen Veerapen:
Special issue on "Stochastic Local Search: Recent developments and trends". Int. Trans. Oper. Res. 27(4): 2253-2254 (2020) - [j54]Holger H. Hoos, Laetitia Jourdan, Marie-Eléonore Kessaci, Thomas Stützle, Nadarajen Veerapen:
Special issue on "Stochastic Local Search: Recent developments and trends". Int. Trans. Oper. Res. 27(5): 2685-2686 (2020) - [j53]Lindsey Burggraaff, Eelke B. Lenselink, Willem Jespers, Jesper E. van Engelen, Brandon J. Bongers, Marina Gorostiola González, Rongfang Liu, Holger H. Hoos, Herman W. T. van Vlijmen, Adriaan P. IJzerman, Gerard J. P. van Westen:
Successive Statistical and Structure-Based Modeling to Identify Chemically Novel Kinase Inhibitors. J. Chem. Inf. Model. 60(9): 4283-4295 (2020) - [j52]Jesper E. van Engelen, Holger H. Hoos:
A survey on semi-supervised learning. Mach. Learn. 109(2): 373-440 (2020) - [c127]Bram M. Renting, Holger H. Hoos, Catholijn M. Jonker:
Automated Configuration of Negotiation Strategies. AAMAS 2020: 1116-1124 - [c126]Alex Serban, Koen van der Blom, Holger H. Hoos, Joost Visser:
Adoption and Effects of Software Engineering Best Practices in Machine Learning. ESEM 2020: 3:1-3:12 - [c125]Yasha Pushak, Holger H. Hoos:
Advanced statistical analysis of empirical performance scaling. GECCO 2020: 236-244 - [c124]Yasha Pushak, Holger H. Hoos:
Golden parameter search: exploiting structure to quickly configure parameters in parallel. GECCO 2020: 245-253 - [c123]Marie Anastacio, Holger H. Hoos:
Combining sequential model-based algorithm configuration with default-guided probabilistic sampling. GECCO Companion 2020: 301-302 - [c122]Sara Tari, Holger H. Hoos, Julie Jacques, Marie-Eléonore Kessaci, Laetitia Jourdan:
Automatic Configuration of a Multi-objective Local Search for Imbalanced Classification. PPSN (1) 2020: 65-77 - [c121]Marie Anastacio, Holger H. Hoos:
Model-Based Algorithm Configuration with Default-Guided Probabilistic Sampling. PPSN (1) 2020: 95-110 - [c120]Chuan Luo, Holger H. Hoos, Shaowei Cai:
PbO-CCSAT: Boosting Local Search for Satisfiability Using Programming by Optimisation. PPSN (1) 2020: 373-389 - [c119]Jesper E. van Engelen, Holger H. Hoos:
Semi-supervised Co-ensembling for AutoML. TAILOR 2020: 229-250 - [i25]Yi Chu, Chuan Luo, Holger H. Hoos, Qingwei Lin, Haihang You:
Improving the Performance of Stochastic Local Search for Maximum Vertex Weight Clique Problem Using Programming by Optimization. CoRR abs/2002.11909 (2020) - [i24]Bram M. Renting, Holger H. Hoos, Catholijn M. Jonker:
Automated Configuration of Negotiation Strategies. CoRR abs/2004.00094 (2020) - [i23]Alex Serban, Koen van der Blom, Holger H. Hoos, Joost Visser:
Adoption and Effects of Software Engineering Best Practices in Machine Learning. CoRR abs/2007.14130 (2020)
2010 – 2019
- 2019
- [j51]Holger H. Hoos, Frank Neumann, Heike Trautmann:
Foreword. Evol. Comput. 27(1): 1-2 (2019) - [j50]Pascal Kerschke, Holger H. Hoos, Frank Neumann, Heike Trautmann:
Automated Algorithm Selection: Survey and Perspectives. Evol. Comput. 27(1): 3-45 (2019) - [j49]Aymeric Blot, Marie-Eléonore Marmion, Laetitia Jourdan, Holger H. Hoos:
Automatic Configuration of Multi-Objective Local Search Algorithms for Permutation Problems. Evol. Comput. 27(1): 147-171 (2019) - [j48]Holger H. Hoos, Laetitia Jourdan, Marie-Eléonore Kessaci, Thomas Stützle, Nadarajen Veerapen:
Special issue on "Stochastic Local Search: Recent developments and trends". Int. Trans. Oper. Res. 26(6): 2580-2581 (2019) - [c118]Camille Pageau, Aymeric Blot, Holger H. Hoos, Marie-Eléonore Kessaci, Laetitia Jourdan:
Configuration of a Dynamic MOLS Algorithm for Bi-objective Flowshop Scheduling. EMO 2019: 565-577 - [c117]Chuan Luo, Holger H. Hoos, Shaowei Cai, Qingwei Lin, Hongyu Zhang, Dongmei Zhang:
Local Search with Efficient Automatic Configuration for Minimum Vertex Cover. IJCAI 2019: 1297-1304 - [c116]Can Wang, Thomas Bäck, Holger H. Hoos, Mitra Baratchi, Steffen Limmer, Markus Olhofer:
Automated Machine Learning for Short-term Electric Load Forecasting. SSCI 2019: 314-321 - [p7]Lars Kotthoff, Chris Thornton, Holger H. Hoos, Frank Hutter, Kevin Leyton-Brown:
Auto-WEKA: Automatic Model Selection and Hyperparameter Optimization in WEKA. Automated Machine Learning 2019: 81-95 - 2018
- [j47]Andrea F. Bocchese, Chris Fawcett, Mauro Vallati, Alfonso Emilio Gerevini, Holger H. Hoos:
Performance robustness of AI planners in the 2014 International Planning Competition. AI Commun. 31(6): 445-463 (2018) - [j46]Pascal Kerschke, Lars Kotthoff, Jakob Bossek, Holger H. Hoos, Heike Trautmann:
Leveraging TSP Solver Complementarity through Machine Learning. Evol. Comput. 26(4) (2018) - [j45]Zongxu Mu, Jérémie Dubois-Lacoste, Holger H. Hoos, Thomas Stützle:
On the empirical scaling of running time for finding optimal solutions to the TSP. J. Heuristics 24(6): 879-898 (2018) - [j44]Katharina Eggensperger, Marius Lindauer, Holger H. Hoos, Frank Hutter, Kevin Leyton-Brown:
Efficient benchmarking of algorithm configurators via model-based surrogates. Mach. Learn. 107(1): 15-41 (2018) - [c115]Nodir Kodirov, Sam Bayless, Fabian Ruffy, Ivan Beschastnikh, Holger H. Hoos, Alan J. Hu:
VNF chain allocation and management at data center scale. ANCS 2018: 125-140 - [c114]Nodir Kodirov, Sam Bayless, Fabian Ruffy, Ivan Beschastnikh, Holger H. Hoos, Alan J. Hu:
VNF chain abstraction for cloud service providers. ANCS 2018: 165-166 - [c113]Holger H. Hoos, Tomás Peitl, Friedrich Slivovsky, Stefan Szeider:
Portfolio-Based Algorithm Selection for Circuit QBFs. CP 2018: 195-209 - [c112]Julieta Martinez, Shobhit Zakhmi, Holger H. Hoos, James J. Little:
LSQ++: Lower Running Time and Higher Recall in Multi-codebook Quantization. ECCV (16) 2018: 508-523 - [c111]Aymeric Blot, Holger H. Hoos, Marie-Eléonore Kessaci, Laetitia Jourdan:
Automatic Configuration of Bi-Objective Optimisation Algorithms: Impact of Correlation Between Objectives. ICTAI 2018: 571-578 - [c110]Lars Kotthoff, Alexandre Fréchette, Tomasz P. Michalak, Talal Rahwan, Holger H. Hoos, Kevin Leyton-Brown:
Quantifying Algorithmic Improvements over Time. IJCAI 2018: 5165-5171 - [c109]Yasha Pushak, Holger H. Hoos:
Algorithm Configuration Landscapes: - More Benign Than Expected? PPSN (2) 2018: 271-283 - [p6]Marius Lindauer, Holger H. Hoos, Frank Hutter, Kevin Leyton-Brown:
Selection and Configuration of Parallel Portfolios. Handbook of Parallel Constraint Reasoning 2018: 583-615 - [p5]Holger H. Hoos, Thomas Stützle:
Empirical Analysis of Randomised Algorithms. Handbook of Approximation Algorithms and Metaheuristics (1) 2018: 225-242 - [p4]Holger H. Hoos, Thomas Stützle:
Stochastic Local Search. Handbook of Approximation Algorithms and Metaheuristics (1) 2018: 297-307 - [i22]Pascal Kerschke, Holger H. Hoos, Frank Neumann, Heike Trautmann:
Automated Algorithm Selection: Survey and Perspectives. CoRR abs/1811.11597 (2018) - [i21]Tijl De Bie, Luc De Raedt, Holger H. Hoos, Padhraic Smyth:
Automating Data Science (Dagstuhl Seminar 18401). Dagstuhl Reports 8(9): 154-181 (2018) - 2017
- [j43]Frank Hutter, Marius Lindauer, Adrian Balint, Sam Bayless, Holger H. Hoos, Kevin Leyton-Brown:
The Configurable SAT Solver Challenge (CSSC). Artif. Intell. 243: 1-25 (2017) - [j42]Marius Lindauer, Holger H. Hoos, Kevin Leyton-Brown, Torsten Schaub:
Automatic construction of parallel portfolios via algorithm configuration. Artif. Intell. 244: 272-290 (2017) - [j41]Mattia Rizzini, Chris Fawcett, Mauro Vallati, Alfonso Emilio Gerevini, Holger H. Hoos:
Static and Dynamic Portfolio Methods for Optimal Planning: An Empirical Analysis. Int. J. Artif. Intell. Tools 26(1): 1760006:1-1760006:27 (2017) - [j40]Lars Kotthoff, Chris Thornton, Holger H. Hoos, Frank Hutter, Kevin Leyton-Brown:
Auto-WEKA 2.0: Automatic model selection and hyperparameter optimization in WEKA. J. Mach. Learn. Res. 18: 25:1-25:5 (2017) - [c108]Andre Biedenkapp, Marius Lindauer, Katharina Eggensperger, Frank Hutter, Chris Fawcett, Holger H. Hoos:
Efficient Parameter Importance Analysis via Ablation with Surrogates. AAAI 2017: 773-779 - [c107]Aymeric Blot, Alexis Pernet, Laetitia Jourdan, Marie-Éléonore Kessaci-Marmion, Holger H. Hoos:
Automatically Configuring Multi-objective Local Search Using Multi-objective Optimisation. EMO 2017: 61-76 - [c106]Sam Bayless, Nodir Kodirov, Ivan Beschastnikh, Holger H. Hoos, Alan J. Hu:
Scalable Constraint-based Virtual Data Center Allocation. IJCAI 2017: 546-554 - [c105]Marius Lindauer, Frank Hutter, Holger H. Hoos, Torsten Schaub:
AutoFolio: An Automatically Configured Algorithm Selector (Extended Abstract). IJCAI 2017: 5025-5029 - [c104]Leslie Pérez Cáceres, Manuel López-Ibáñez, Holger H. Hoos, Thomas Stützle:
An Experimental Study of Adaptive Capping in irace. LION 2017: 235-250 - [e4]Pavel Brazdil, Joaquin Vanschoren, Frank Hutter, Holger H. Hoos:
Proceedings of the International Workshop on Automatic Selection, Configuration and Composition of Machine Learning Algorithms co-located with the European Conference on Machine Learning & Principles and Practice of Knowledge Discovery in Databases, AutoML@PKDD/ECML 2017, Skopje, Macedonia, September 22, 2017. CEUR Workshop Proceedings 1998, CEUR-WS.org 2017 [contents] - [i20]Chris Cameron, Holger H. Hoos, Kevin Leyton-Brown, Frank Hutter:
OASC-2017: *Zilla Submission. OASC 2017: 15-18 - [i19]Katharina Eggensperger, Marius Lindauer, Holger H. Hoos, Frank Hutter, Kevin Leyton-Brown:
Efficient Benchmarking of Algorithm Configuration Procedures via Model-Based Surrogates. CoRR abs/1703.10342 (2017) - [i18]Chris Fawcett, Lars Kotthoff, Holger H. Hoos:
Hot-Rodding the Browser Engine: Automatic Configuration of JavaScript Compilers. CoRR abs/1707.04245 (2017) - 2016
- [j39]Ashiqur R. KhudaBukhsh, Lin Xu, Holger H. Hoos, Kevin Leyton-Brown:
SATenstein: Automatically building local search SAT solvers from components. Artif. Intell. 232: 20-42 (2016) - [j38]Bernd Bischl, Pascal Kerschke, Lars Kotthoff, Marius Lindauer, Yuri Malitsky, Alexandre Fréchette, Holger H. Hoos, Frank Hutter, Kevin Leyton-Brown, Kevin Tierney, Joaquin Vanschoren:
ASlib: A benchmark library for algorithm selection. Artif. Intell. 237: 41-58 (2016) - [j37]Chris Fawcett, Holger H. Hoos:
Analysing differences between algorithm configurations through ablation. J. Heuristics 22(4): 431-458 (2016) - [c103]