| 2026 | AAAI | Neural Architecture and Hyperparameter Selection Through Meta-Learning on Time Series. | Erfan Moeini, Christopher Vox, Marie Anastacio, Wadie Skaf, Mitra Baratchi, Holger H. Hoos |
| 2026 | GECCO | Improving Evaluation of Recombination-based Cartesian Genetic Programming. | Duy Long Tran, Anja Jankovic, Marie Anastacio, Holger H. Hoos, Roman Kalkreuth |
| 2026 | WACV | Towards Consistent and Efficient Decision-Based Attacks. | Henning Duwe, Anna L. Mnz, Holger H. Hoos |
| 2026 | SAT | Sustainable Benchmarking Tool (Tool Paper). | Ashlin Iser, Marie Anastacio, Tho Matricon, Laurent Simon, Holger H. Hoos |
| 2025 | AAAI | KernelMatmul: Scaling Gaussian Processes to Large Time Series. | Tilman Hoffbauer, Holger H. Hoos, Jakob Bossek |
| 2025 | AAAI | Dynamic Algorithm Termination for Branch-and-Bound-based Neural Network Verification. | Konstantin Kaulen, Matthias Knig, Holger H. Hoos |
| 2025 | GECCO | TinyverseGP: Towards a Modular Cross-domain Benchmarking Framework for Genetic Programming. | Roman Kalkreuth, Fabrcio Olivetti de Frana, Anja Jankovic, Marie Anastacio, Julian Dierkes, Zdenek Vascek, Holger H. Hoos |
| 2024 | AAAI | Accelerating Adversarially Robust Model Selection for Deep Neural Networks via Racing. | Matthias Knig, Holger H. Hoos, Jan N. van Rijn |
| 2024 | GECCO | Multi-objective Ranking using Bootstrap Resampling. | Jeroen Rook, Holger H. Hoos, Heike Trautmann |
| 2024 | SAT | Revisiting SATZilla Features in 2024. | Hadar Shavit, Holger H. Hoos |
| 2023 | AAAI | Critically Assessing the State of the Art in CPU-based Local Robustness Verification. | Matthias Knig, Annelot W. Bosman, Holger H. Hoos, Jan N. van Rijn |
| 2021 | CP | Statistical Comparison of Algorithm Performance Through Instance Selection. | Tho Matricon, Marie Anastacio, Nathanal Fijalkow, Laurent Simon, Holger H. Hoos |
| 2021 | SAT | Efficient Local Search for Pseudo Boolean Optimization. | Zhendong Lei, Shaowei Cai, Chuan Luo, Holger H. Hoos |
| 2020 | ESEM | Adoption and Effects of Software Engineering Best Practices in Machine Learning. | Alex Serban, Koen van der Blom, Holger H. Hoos, Joost Visser |
| 2020 | GECCO | Combining sequential model-based algorithm configuration with default-guided probabilistic sampling. | Marie Anastacio, Holger H. Hoos |
| 2020 | GECCO | Advanced statistical analysis of empirical performance scaling. | Yasha Pushak, Holger H. Hoos |
| 2020 | GECCO | Golden parameter search: exploiting structure to quickly configure parameters in parallel. | Yasha Pushak, Holger H. Hoos |
| 2020 | PPSN | Model-Based Algorithm Configuration with Default-Guided Probabilistic Sampling. | Marie Anastacio, Holger H. Hoos |
| 2020 | PPSN | PbO-CCSAT: Boosting Local Search for Satisfiability Using Programming by Optimisation. | Chuan Luo, Holger H. Hoos, Shaowei Cai |
| 2020 | PPSN | Automatic Configuration of a Multi-objective Local Search for Imbalanced Classification. | Sara Tari, Holger H. Hoos, Julie Jacques, Marie-Elonore Kessaci, Laetitia Jourdan |
| 2019 | EMO | Configuration of a Dynamic MOLS Algorithm for Bi-objective Flowshop Scheduling. | Camille Pageau, Aymeric Blot, Holger H. Hoos, Marie-Elonore Kessaci, Laetitia Jourdan |
| 2019 | IJCAI | Local Search with Efficient Automatic Configuration for Minimum Vertex Cover. | Chuan Luo, Holger H. Hoos, Shaowei Cai, Qingwei Lin, Hongyu Zhang, Dongmei Zhang |
| 2018 | CP | Portfolio-Based Algorithm Selection for Circuit QBFs. | Holger H. Hoos, Toms Peitl, Friedrich Slivovsky, Stefan Szeider |
| 2018 | ECCV | LSQ++: Lower Running Time and Higher Recall in Multi-codebook Quantization. | Julieta Martinez, Shobhit Zakhmi, Holger H. Hoos, James J. Little |
| 2018 | IJCAI | Quantifying Algorithmic Improvements over Time. | Lars Kotthoff, Alexandre Frchette, Tomasz P. Michalak, Talal Rahwan, Holger H. Hoos, Kevin Leyton-Brown |
| 2018 | ICTAI | Automatic Configuration of Bi-Objective Optimisation Algorithms: Impact of Correlation Between Objectives. | Aymeric Blot, Holger H. Hoos, Marie-Elonore Kessaci, Laetitia Jourdan |
| 2018 | PPSN | Algorithm Configuration Landscapes: - More Benign Than Expected? | Yasha Pushak, Holger H. Hoos |
| 2017 | AAAI | Efficient Parameter Importance Analysis via Ablation with Surrogates. | Andre Biedenkapp, Marius Lindauer, Katharina Eggensperger, Frank Hutter, Chris Fawcett, Holger H. Hoos |
| 2017 | EMO | Automatically Configuring Multi-objective Local Search Using Multi-objective Optimisation. | Aymeric Blot, Alexis Pernet, Laetitia Jourdan, Marie-lonore Kessaci-Marmion, Holger H. Hoos |
| 2017 | IJCAI | Scalable Constraint-based Virtual Data Center Allocation. | Sam Bayless, Nodir Kodirov, Ivan Beschastnikh, Holger H. Hoos, Alan J. Hu |
| 2017 | IJCAI | AutoFolio: An Automatically Configured Algorithm Selector (Extended Abstract). | Marius Lindauer, Frank Hutter, Holger H. Hoos, Torsten Schaub |
| 2016 | AAAI | Using the Shapley Value to Analyze Algorithm Portfolios. | Alexandre Frchette, Lars Kotthoff, Tomasz P. Michalak, Talal Rahwan, Holger H. Hoos, Kevin Leyton-Brown |
| 2016 | ECCV | Revisiting Additive Quantization. | Julieta Martinez, Joris Clement, Holger H. Hoos, James J. Little |
| 2016 | ECCV | Solving Multi-codebook Quantization in the GPU. | Julieta Martinez, Holger H. Hoos, James J. Little |
| 2016 | GECCO | Taming the Complexity Monster or: How I learned to Stop Worrying and Love Hard Problems. | Holger H. Hoos |
| 2016 | ICCAD | Scalable, high-quality, SAT-based multi-layer escape routing. | Sam Bayless, Holger H. Hoos, Alan J. Hu |
| 2016 | IJCAI | Bias in Algorithm Portfolio Performance Evaluation. | Chris Cameron, Holger H. Hoos, Kevin Leyton-Brown |
| 2015 | AAAI | SAT Modulo Monotonic Theories. | Sam Bayless, Noah Bayless, Holger H. Hoos, Alan J. Hu |
| 2015 | AAAI | Efficient Benchmarking of Hyperparameter Optimizers via Surrogates. | Katharina Eggensperger, Frank Hutter, Holger H. Hoos, Kevin Leyton-Brown |
| 2015 | AAAI | AutoFolio: Algorithm Configuration for Algorithm Selection. | Marius Lindauer, Holger H. Hoos, Frank Hutter, Torsten Schaub |
| 2015 | GECCO | On the Empirical Scaling Behaviour of State-of-the-art Local Search Algorithms for the Euclidean TSP. | Jrmie Dubois-Lacoste, Holger H. Hoos, Thomas Sttzle |
| 2015 | GECCO | Empirical Scaling Analyser: An Automated System for Empirical Analysis of Performance Scaling. | Zongxu Mu, Holger H. Hoos |
| 2015 | IJCAI | Algorithm Runtime Prediction: Methods and Evaluation (Extended Abstract). | Frank Hutter, Lin Xu, Holger H. Hoos, Kevin Leyton-Brown |
| 2015 | IJCAI | On the Empirical Time Complexity of Random 3-SAT at the Phase Transition. | Zongxu Mu, Holger H. Hoos |
| 2015 | ICTAI | Portfolio Methods for Optimal Planning: An Empirical Analysis. | Mattia Rizzini, Chris Fawcett, Mauro Vallati, Alfonso Emilio Gerevini, Holger H. Hoos |
| 2015 | WACV | Bank of Quantization Models: A Data-Specific Approach to Learning Binary Codes for Large-Scale Retrieval Applications. | Frederick Tung, Julieta Martinez, Holger H. Hoos, James J. Little |
| 2014 | ECAI | Surrogate Benchmarks for Hyperparameter Optimization. | Katharina Eggensperger, Frank Hutter, Holger H. Hoos, Kevin Leyton-Brown |
| 2014 | ICML | An Efficient Approach for Assessing Hyperparameter Importance. | Frank Hutter, Holger H. Hoos, Kevin Leyton-Brown |
| 2013 | FMCAD | Efficient modular SAT solving for IC3. | Sam Bayless, Celina G. Val, Thomas Ball, Holger H. Hoos, Alan J. Hu |
| 2013 | GECCO | An evaluation of sequential model-based optimization for expensive blackbox functions. | Frank Hutter, Holger H. Hoos, Kevin Leyton-Brown |
| 2013 | GECCO | Ordered racing protocols for automatically configuring algorithms for scaling performance. | James Styles, Holger H. Hoos |
| 2013 | KDD | Auto-WEKA: combined selection and hyperparameter optimization of classification algorithms. | Chris Thornton, Frank Hutter, Holger H. Hoos, Kevin Leyton-Brown |
| 2013 | SoCS | Automatic Generation of Efficient Domain-Optimized Planners from Generic Parametrized Planners. | Mauro Vallati, Chris Fawcett, Alfonso Gerevini, Holger H. Hoos, Alessandro Saetti |
| 2012 | AAAI | Predicting Satisfiability at the Phase Transition. | Lin Xu, Holger H. Hoos, Kevin Leyton-Brown |
| 2012 | ICLP | aspeed: ASP-based Solver Scheduling. | Holger H. Hoos, Roland Kaminski, Torsten Schaub, Marius Schneider |
| 2012 | SAT | Evaluating Component Solver Contributions to Portfolio-Based Algorithm Selectors. | Lin Xu, Frank Hutter, Holger H. Hoos, Kevin Leyton-Brown |
| 2011 | SAT | Captain Jack: New Variable Selection Heuristics in Local Search for SAT. | Dave A. D. Tompkins, Adrian Balint, Holger H. Hoos |
| 2010 | AAAI | Hydra: Automatically Configuring Algorithms for Portfolio-Based Selection. | Lin Xu, Holger H. Hoos, Kevin Leyton-Brown |
| 2010 | CPAIOR | Automated Configuration of Mixed Integer Programming Solvers. | Frank Hutter, Holger H. Hoos, Kevin Leyton-Brown |
| 2010 | SAT | Dynamic Scoring Functions with Variable Expressions: New SLS Methods for Solving SAT. | Dave A. D. Tompkins, Holger H. Hoos |
| 2009 | GECCO | An experimental investigation of model-based parameter optimisation: SPO and beyond. | Frank Hutter, Holger H. Hoos, Kevin Leyton-Brown, Kevin P. Murphy |
| 2009 | IJCAI | SATenstein: Automatically Building Local Search SAT Solvers from Components. | Ashiqur R. KhudaBukhsh, Lin Xu, Holger H. Hoos, Kevin Leyton-Brown |
| 2007 | AAAI | Automatic Algorithm Configuration Based on Local Search. | Frank Hutter, Holger H. Hoos, Thomas Sttzle |
| 2007 | CP | : The Design and Analysis of an Algorithm Portfolio for SAT. | Lin Xu, Frank Hutter, Holger H. Hoos, Kevin Leyton-Brown |
| 2007 | CP | Hierarchical Hardness Models for SAT. | Lin Xu, Holger H. Hoos, Kevin Leyton-Brown |
| 2007 | FMCAD | Boosting Verification by Automatic Tuning of Decision Procedures. | Frank Hutter, Domagoj Babic, Holger H. Hoos, Alan J. Hu |
| 2007 | ISMB | Efficient parameter estimation for RNA secondary structure prediction. | Mirela Andronescu, Anne Condon, Holger H. Hoos, David H. Mathews, Kevin P. Murphy |
| 2006 | AI | On the Quality and Quantity of Random Decisions in Stochastic Local Search for SAT. | Dave A. D. Tompkins, Holger H. Hoos |
| 2006 | CP | Performance Prediction and Automated Tuning of Randomized and Parametric Algorithms. | Frank Hutter, Youssef Hamadi, Holger H. Hoos, Kevin Leyton-Brown |
| 2005 | IJCAI | Efficient Stochastic Local Search for MPE Solving. | Frank Hutter, Holger H. Hoos, Thomas Sttzle |
| 2004 | CP | Understanding Random SAT: Beyond the Clauses-to-Variables Ratio. | Eugene Nudelman, Kevin Leyton-Brown, Holger H. Hoos, Alex Devkar, Yoav Shoham |
| 2004 | ISAIM | Warped Landscapes and Random Acts of SAT Solving. | Dave A. D. Tompkins, Holger H. Hoos |
| 2004 | PPSN | Search Space Features Underlying the Performance of Stochastic Local Search Algorithms for MAX-SAT. | Holger H. Hoos, Kevin Smyth, Thomas Sttzle |
| 2004 | SAT | UBCSAT: An Implementation and Experimentation Environment for SLS Algorithms for SAT & MAX-SAT. | Dave A. D. Tompkins, Holger H. Hoos |
| 2004 | SAT | UBCSAT: An Implementation and Experimentation Environment for SLS Algorithms for SAT and MAX-SAT. | Dave A. D. Tompkins, Holger H. Hoos |
| 2003 | AI | Stochastic Local Search for Multiprocessor Scheduling for Minimum Total Tardiness. | Michael Pavlin, Holger H. Hoos, Thomas Sttzle |
| 2003 | AI | An Improved Ant Colony Optimisation Algorithm for the 2D HP Protein Folding Problem. | Alena Shmygelska, Holger H. Hoos |
| 2003 | AI | Iterated Robust Tabu Search for MAX-SAT. | Kevin Smyth, Holger H. Hoos, Thomas Sttzle |
| 2003 | AI | Scaling and Probabilistic Smoothing: Dynamic Local Search for Unweighted MAX-SAT. | Dave A. D. Tompkins, Holger H. Hoos |
| 2003 | AI | Hybrid Randomised Neighbourhoods Improve Stochastic Local Search for DNA Code Design. | Dan C. Tulpan, Holger H. Hoos |
| 2003 | CP | Using Stochastic Local Search to Solve Quantified Boolean Formulae. | Ian P. Gent, Holger H. Hoos, Andrew G. D. Rowley, Kevin Smyth |
| 2003 | SAC | Inference of Transcriptional Regulation Relationships from Gene Expression Data. | Andrew Tae-Jun Kwon, Holger H. Hoos, Raymond T. Ng |
| 2002 | AAAI | An Adaptive Noise Mechanism for WalkSAT. | Holger H. Hoos |
| 2002 | AAAI | A Mixture-Model for the Behaviour of SLS Algorithms for SAT. | Holger H. Hoos |
| 2002 | CP | Scaling and Probabilistic Smoothing: Efficient Dynamic Local Search for SAT. | Frank Hutter, Dave A. D. Tompkins, Holger H. Hoos |
| 2002 | DNA | From RNA Secondary Structure to Coding Theory: A Combinatorial Approach. | Christine E. Heitsch, Anne Condon, Holger H. Hoos |
| 2002 | DNA | Stochastic Local Search Algorithms for DNA Word Design. | Dan C. Tulpan, Holger H. Hoos, Anne Condon |
| 2001 | IJCAI | Bidding Languages for Combinatorial Auctions. | Craig Boutilier, Holger H. Hoos |
| 2000 | AAAI | Solving Combinatorial Auctions Using Stochastic Local Search. | Holger H. Hoos, Craig Boutilier |
| 1999 | AAAI | Morphing: Combining Structure and Randomness. | Ian P. Gent, Holger H. Hoos, Patrick Prosser, Toby Walsh |
| 1999 | AAAI | On the Run-time Behaviour of Stochastic Local Search Algorithms for SAT. | Holger H. Hoos |
| 1999 | IJCAI | To Encode or Not to Encode - Linear Planning. | Ronen I. Brafman, Holger H. Hoos |
| 1999 | IJCAI | SAT-Encodings, Search Space Structure, and Local Search Performance. | Holger H. Hoos |
| 1999 | KI | Systematic vs. Local Search for SAT. | Holger H. Hoos, Thomas Sttzle |
| 1999 | UAI | Reasoning With Conditional Ceteris Paribus Preference Statements. | Craig Boutilier, Ronen I. Brafman, Holger H. Hoos, David Poole |
| 1998 | CP | Some Surprising Regularities in the Behaviour of Stochastic Local Search. | Holger H. Hoos, Thomas Sttzle |
| 1998 | UAI | Evaluating Las Vegas Algorithms: Pitfalls and Remedies. | Holger H. Hoos, Thomas Sttzle |
| 1997 | ICEC | MAX-MIN Ant System and local search for the traveling salesman problem. | Thomas Sttzle, Holger H. Hoos |
| 1996 | KI | Solving Hard Combinatorial Problems with GSAT - A Case Study. | Holger H. Hoos |
| 1994 | ECAI | GSAT versus Simulated Annealing. | Antje Beeringer, Gerd Aschemann, Holger H. Hoos, Michael Metzger, Andreas Weiss |