The goal of this project is the development of methods for algorithm selection and configuration under resource constraints. Especially of interest are scenarios where a single evaluation of an algorithm is expensive. We address the case where many competing candidate algorithms are available and each algorithm has specific hyperparameters that have to be tuned to obtain the best possible outcome. It is not possible to exhaustively search through this space, because the number of configurations that can be evaluated during the optimisation is heavily limited due to their long runtimes. In a typical situation the algorithm is a machine learning method that is applied on a regression or classification data set. The optimisation goal is to find a machine learning method from a set of candidates and configure its hyperparameters to achieve the best possible prediction quality.
Model-based optimisation (MBO) addresses this challenge. It uses a regression model as a surrogate to approximate the objective function. For example, the prediction quality of a machine learning algorithm on a given task is predicted by a Gaussian process regression. The predictions obtained from the surrogate model help to move quickly to regions in the search space with promising prediction quality. This reduces the number of expensive evaluations during the optimisation. Due to the enormous number of possible configurations, the overall MBO wall-clock runtime still can be unreasonably long. The use of parallel computing systems and efficient resource utilisation becomes essential.
To address these challenges, we have developed the framework resource-aware model-based optimization (RAMBO) with scheduling for heterogeneous runtimes. It extends MBO to work on parallel systems while maximising resource utilisation. Thus, methods applied for the optimisation to achieve high efficiency of embedded systems can be adapted for improving the parallel execution of machine learning tasks in modern computing systems. In the third phase, we want to investigate scenarios with additional challenges, such as time-varying objective functions, insufficient prediction quality due to small sample sizes, and data streams. Efficient solutions for these challenges can be obtained by extending the RAMBO framework and by further improving the scheduling strategies. Time-varying objective functions are common in the real world, i.e., the best-performing algorithm configuration changes over time, which is generally called concept drift. For small sample sizes, we will investigate the combination of real data and additional simulated data. For data streams the machine learning method will adapt to changes in order to optimise the prediction quality. These extensions of RAMBO make it usable for a wide range of applications, including data rate prediction for mobile phones as well as traffic analysis and prediction.
To evaluate the new methods, we use established benchmarks that provide a controlled environment to draw objective conclusions. In a second step we will also verify our proposed approach with real-world data. In addition to the developed methods themselves, a major outcome of this project are self-contained and well-documented open-source software packages, assuring the reproducibility of the experiments and future usability for other researchers around the world.
| Bommert/etal/2022a |
Bommert, Andrea and Rahnenführer, Jörg and Lang, Michel.
Employing an Adjusted Stability Measure for Multi-criteria Model Fitting on Data Sets with Similar Features.
In
Nicosia G. et al. (editors),
Machine Learning, Optimization, and Data Science,
pages 81-92,
Springer,
2022.
|
| Richter/etal/2022a |
Richter, Jakob and Friede, Tim and Rahnenführer, Jörg.
Improving adaptive seamless designs through Bayesian optimization.
In
Biometrical Journal,
Vol. 64,
No. 5,
pages 948-963,
2022.
|
| Binder/etal/2021a |
Martin Binder and Florian Pfisterer and Michel Lang and Lennart Schneider and Lars Kotthoff and Bernd Bischl.
mlr3pipelines - Flexible Machine Learning Pipelines in R.
In
Journal of Machine Learning Research,
Vol. 22,
No. 184,
pages 1-7,
2021.
|
| Bischl/etal/2021a |
Bernd Bischl and Martin Binder and Michel Lang and Tobias Pielok and Jakob Richter and Stefan Coors and Janek Thomas and Theresa Ullmann and Marc Becker and Anne-Laure Boulesteix and Difan Deng and Marius Lindauer.
Hyperparameter Optimization: Foundations, Algorithms, Best Practices and Open Challenges.
2021.
|
| Bischl/etal/2021b |
Bischl, Bernd and Casalicchio, Giuseppe and Feurer, Matthias and Gijsbers, Pieter and Hutter, Frank and Lang, Michel and Gomes Mantovani, Rafael and van Rijn, Jan and Vanschoren, Joaquin.
OpenML Benchmarking Suites.
In
J. Vanschoren and S. Yeung (editors),
Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks,
Vol. 1,
2021.
|
| Bommert/etal/2021a |
Bommert, Andrea and Welchowski, Thomas and Schmid, Matthias and Rahnenführer, Jörg.
Benchmark of filter methods for feature selection in high-dimensional gene expression survival data.
In
Briefings in Bioinformatics,
pages bbab354,
2021.
|
| Bommert/Lang/2021a |
Bommert, Andrea and Lang, Michel.
stabm: Stability Measures for Feature Selection.
In
Journal of Open Source Software,
Vol. 6,
No. 59,
pages 3010,
2021.
|
| Chen/etal/2021a |
Chen, Jian-Jia and Huang, Wen-Hung and von der Brüggen, Georg and Ueter, Niklas.
On the Formalism and Properties of Timing Analyses in Real-Time Embedded Systems.
In
A Journey of Embedded and Cyber-Physical Systems - Essays Dedicated to Peter Marwedel on the Occasion of His 70th Birthday,
pages 37--55,
2021.
|
| Jagdhuber/Rahnenfuehrer/2021a |
Jagdhuber, Rudolf and Rahnenführer, Jörg.
Implications on Feature Detection When Using the Benefit–Cost Ratio.
In
SN Computer Science,
Vol. 2,
No. 4,
pages 316,
2021.
|
| Madjar/etal/2021a |
Madjar, Katrin and Zucknick, Manuela and Ickstadt, Katja and Rahnenführer, Jörg.
Combining heterogeneous subgroups with graph-structured variable selection priors for Cox regression.
In
BMC Bioinform.,
Vol. 22,
No. 1,
pages 586,
2021.
|
| Marwedel/2021b |
Marwedel, Peter.
Eingebettete Systeme - Grundlagen Eingebetteter Systeme in Cyber-Physikalischen Systemen.
Springer,
2021.
|
| Shi/etal/2021a |
Shi, Junjie and Bian, Jiang and Richter, Jakob and Chen, Kuan-Hsun and Rahnenführer, Jörg and Xiong, Haoyi and Chen, Jian-Jia.
MODES: model-based optimization on distributed embedded systems.
In
Machine Learning (Journal Track of ECML/PKDD),
Vol. 110,
No. 6,
pages 1527--1547,
2021.
|
| Shi/etal/2021c |
Shi, Junjie and Ueter, Niklas and von der Brüggen, Georg and Chen, Jian-Jia.
Graph-Based Optimizations for Multiprocessor Nested Resource Sharing.
In
Proceedings of the 27th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications, RTCSA,
2021.
|
| Sonabend/etal/2021a |
Raphael Sonabend and Franz J Király and Andreas Bender and Bernd Bischl and Michel Lang.
mlr3proba: An R Package for Machine Learning in Survival Analysis.
In
Bioinformatics,
2021.
|
| Bommert/etal/2020a |
Bommert, Andrea and Sun, Xudong and Bischl, Bernd and Rahnenführer, Jörg and Lang, Michel.
Benchmark for Filter Methods for Feature Selection in High-Dimensional Classification Data.
In
Computational Statistics & Data Analysis,
Vol. 143,
pages 106839,
2020.
|
| Bommert/Rahnenfuehrer/2020a |
Bommert, Andrea and Rahnenführer, Jörg.
Adjusted Measures for Feature Selection Stability for Data Sets with Similar Features.
In
Nicosia, Giuseppe and Ojha, Varun and La Malfa, Emanuele and Jansen, Giorgio and Sciacca, Vincenzo and Pardalos, Panos and Giuffrida, Giovanni and Umeton, Renato (editors),
Machine Learning, Optimization, and Data Science,
pages 203-214,
Springer,
2020.
|
| Chen/etal/2020f |
Chen, Jian-Jia and Shi, Junjie and von der Brüggen, Georg and Ueter, Niklas.
Scheduling of Real-Time Tasks with Multiple Critical Sections in Multiprocessor Systems.
In
IEEE Transactions on Computers,
2020.
|
| Jagdhuber/etal/2020a |
Jagdhuber, Rudolf and Lang, Michel and Stenzl, Arnulf and Neuhaus, Jochen and Rahnenführer, Jörg.
Cost-Constrained feature selection in binary classification: adaptations for greedy forward selection and genetic algorithms.
In
BMC Bioinformatics,
Vol. 21,
No. 1,
pages 26,
2020.
|
| Jagdhuber/etal/2020b |
Jagdhuber, Rudolf and Lang, Michel and Rahnenführer, Jörg.
Feature Selection Methods for Cost-Constrained Classification in Random Forests.
2020.
|
| Marwedel/Mitra/2020a |
P. Marwedel and T. Mitra and M. E. Grimheden and H. A. Andrade.
Survey on Education for Cyber-Physical Systems.
In
IEEE Design & Test,
Vol. 37,
No. 6,
pages 56-70,
2020.
|
| Marwedel/Mitra/2020b |
P. Marwedel and T. Mitra and M. E. Grimheden and H. A. Andrade.
Guest Editors’ Introduction: Guest Editors’ Introduction: Education for Cyber–Physical Systems.
In
IEEE Design & Test,
Vol. 37,
No. 6,
pages 5-7,
2020.
|
| Nodoushan/Safaei/2020a |
Mostafa Jafari-Nodoushan and Bardia Safaei and Alireza Ejlali and Jian-Jia Chen.
Leakage-Aware Battery Lifetime Analysis Using the Calculus of Variations.
In
IEEE Transactions on Circuits and Systems I: Regular Papers,
Vol. 67,
No. 12,
pages 4829-4841,
2020.
|
| Richter/etal/2020a |
Richter, Jakob and Shi, Junjie and Chen, Jian-Jia and Rahnenführer, Jörg and Lang, Michel.
Model-Based Optimization with Concept Drifts.
In
Proceedings of the 2020 Genetic and Evolutionary Computation Conference,
pages 877?885,
New York, NY, USA,
Association for Computing Machinery,
2020.
|
| Richter/Shi/2020a |
Richter, Jakob and Shi, Junjie and Chen, Jian-Jia and Rahnenführer, Jörg and Lang, Michel.
Model-based Optimization with Concept Drifts.
In
The Genetic and Evolutionary Computation Conference (GECCO),
2020.
|
| Schoenberger/etal/2020a |
Schönberger, Lea and von der Brüggen, Georg and Chen, Kuan-Hsun and Sliwa, Benjamin and Youssef, Hazem and Ramachandran, Aswin and Wietfeld, Christian and ten Hompel, Michael and Chen, Jian-Jia.
Offloading Safety- and Mission-Critical Tasks via Unreliable Connections.
In
32nd Euromicro Conference on Real-Time Systems (ECRTS),
2020.
|
| Schwitalla/Schoenberger/2020a |
Schwitalla, Sebastian and Schoenberger, Lea and Chen, Jian-Jia.
Priority-Preserving Optimization of Status Quo ID-Assignments in Controller Area Network.
In
Design, Automation and Test in Europe Conference (DATE),
IEEE,
2020.
|
| Kotthaus/etal/2019a |
Tözün, Pinar and Kotthaus, Helena.
Scheduling Data-Intensive Tasks on Heterogeneous Many Cores.
In
IEEE Data Engineering Bulletin,
Vol. 42,
No. 1,
pages 61-72,
2019.
|
| Kotthaus/etal/2019b |
Kotthaus, Helena and Schönberger, Lea and Lang, Andreas and Chen, Jian-Jia and Marwedel, Peter.
Can Flexible Multi-Core Scheduling Help to Execute Machine Learning Algorithms Resource-Efficiently?.
In
22nd International Workshop on Software and Compilers for Embedded Systems,
pages 59-62,
ACM,
2019.
|
| Kotthaus/Vitek/2019c |
Kotthaus, Helena and Vitek, Jan.
Typical Mistakes in Data Science: Should you Trust my Model?.
In
Abstract Booklet of the International R User Conference (UseR!),
Toulouse, France,
2019.
|
| Lang/etal/2019a |
Lang, Michel and Binder, Martin and Richter, Jakob and Schratz, Patrick and Pfisterer, Florian and Coors, Stefan and Au, Quay and Casalicchio, Giuseppe and Kotthoff, Lars and Bischl, Bernd.
Mlr3: A Modern Object-Oriented Machine Learning Framework in R.
In
Journal of Open Source Software,
Vol. 4,
No. 44,
pages 1903,
2019.
|
| Richter/etal/2019a |
Richter, Jakob and Madjar, Katrin and Rahnenführer, Jörg.
Model-based optimization of subgroup weights for survival analysis.
In
Bioinformatics,
Vol. 35,
No. 14,
pages i484-i491,
2019.
|
| Shi/etal/2019a |
Shi, Junjie and Ueter, Niklas and von der Brüggen, Georg and Chen, Jian-jia.
Multiprocessor Synchronization of Periodic Real-Time Tasks Using Dependency Graphs.
In
2019 IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS),
pages 279--292,
IEEE,
2019.
|
| Shi/etal/2019b |
Shi, Junjie and Ueter, Niklas and von der Brüggen, Georg and Chen, Jian-Jia.
Partitioned Scheduling for Dependency Graphs in Multiprocessor Real-Time Systems.
In
Proceedings of the 25th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications, RTCSA,
IEEE,
2019.
|
| Chen/etal/2018f |
Chen, Jian-Jia and von der Brueggen, Georg and Shi, Junjie and Ueter, Niklas.
Dependency Graph Approach for Multiprocessor Real-Time Synchronization.
In
Real-Time Systems Symposium (RTSS),
2018.
|
| Kotthaus/etal/2018a |
Kotthaus, Helena and Lang, Andreas and Marwedel, Peter.
Optimizing Parallel R Programs via Dynamic Scheduling Strategies.
In
Abstract Booklet of the International R User Conference (UseR!),
Brisbane, Australia,
2018.
|
| Marwedel/2018a |
Marwedel, P..
Design of Cyber - Physical Systems.
Global Initiative of Academic Networks (GIAN), Course 270, Ministryof Human Resource Development, Government of India,
Indian Institute of Technology Delhi,
2018.
|
| Marwedel/2018b |
Marwedel, Peter.
Embedded System Design - Embedded Systems Foundations of Cyber-Physical Systems, and the Internet of Things.
Springer,
2018.
|
| Richter/etal/2018a |
Jakob Richter, Katrin Madjar, Jörg Rahnenführer.
Model-Based Optimization of Subgroup Weights for Survival Analysis.
No. 3,
Faculty of Statistics, TU Dortmund University,
2018.
|
| Bischl/etal/2017a |
Bischl, Bernd and Richter, Jakob and Bossek, Jakob and Horn, Daniel and Thomas, Janek and Lang, Michel.
mlrMBO: A Modular Framework for Model-Based Optimization of Expensive Black-Box Functions.
In
arXiv preprint arXiv:1703.03373,
2017.
|
| Bommert/etal/2017a |
Andrea Bommert and Jörg Rahnenführer and Michel Lang.
A multi-criteria approach to find predictive and sparse models with stable feature selection for high-dimensional data.
In
Computational and Mathematical Methods in Medicine,
Vol. 2017,
pages 1--18,
2017.
|
| Kotthaus/2017b |
Kotthaus, Helena and Lang, Andreas and Neugebauer, Olaf and Marwedel, Peter.
R goes Mobile: Efficient Scheduling for Parallel R Programs on Heterogeneous Embedded Systems.
In
Abstract Booklet of the International R User Conference (UseR!),
pages 74,
Brussels, Belgium,
2017.
|
| Kotthaus/etal/2017a |
Kotthaus, Helena and Richter, Jakob and Lang, Andreas and Thomas, Janek and Bischl, Bernd and Marwedel, Peter and Rahnenführer, Jörg and Lang, Michel.
RAMBO: Resource-Aware Model-Based Optimization with Scheduling for Heterogeneous Runtimes and a Comparison with Asynchronous Model-Based Optimization.
In
Procs. of the 11th LION,
pages 180-195,
2017.
|
| Marwedel/etal/2017a |
Marwedel, Peter and Falk, Heiko and Neugebauer, Olaf.
Memory-Aware Optimization of Embedded Software for Multiple Objectives.
Vol. Handbook of Hardware/Software Codesign,
pages 1-37,
Springer,
2017.
|
| Neugebauer/etal/2017a |
Neugebauer, Olaf and Marwedel, Peter and Kühn, Roland and Engel, Michael.
Quality Evaluation Strategies for Approximate Computing in Embedded Systems.
In
Technological Innovation for Smart Systems: 8th IFIP WG 5.5/SOCOLNET Advanced Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2017,
pages 203--210,
Costa de Caparica, Portugal,
2017.
|
| Richter/2017b |
Richter, Jakob and Rahnenführer, Jörg and Lang, Michel.
mlrHyperopt: Effortless and collaborative hyperparameter optimization experiments.
In
Abstract Booklet of the International R User Conference (UseR!),
pages 78,
Brussels, Belgium,
2017.
|
| Bischl/etal/2016a |
Bernd Bischl and Michel Lang and Lars Kotthoff and Julia Schiffner and Jakob Richter and Erich Studerus and Giuseppe Casalicchio and Zachary M. Jones.
mlr: Machine Learning in R.
In
Journal of Machine Learning Research,
Vol. 17,
No. 170,
pages 1-5,
2016.
|
| Kotthaus/etal/2016a |
Kotthaus, Helena and Richter, Jakob and Lang, Andreas and Lang, Michel and Marwedel, Peter.
Resource-Aware Scheduling Strategies for Parallel Machine Learning R Programs through RAMBO.
In
Abstract Booklet of the International R User Conference (UseR!),
pages 195,
Stanford University, Palo Alto, California,
2016.
|
| Richter/etal/2016a |
Richter, Jakob and Lang, Michel and Bischl, Bernd.
mlrMBO: A Toolbox for Model-Based Optimization of Expensive Black-Box Functions.
In
Abstract Booklet of the International R User Conference (UseR!),
pages 202,
Stanford University, Palo Alto, California,
2016.
|
| Richter/etal/2016b |
Richter, Jakob and Kotthaus, Helena and Bischl, Bernd and Marwedel, Peter and Rahnenführer, Jörg and Lang, Michel.
Faster Model-Based Optimization through Resource-Aware Scheduling Strategies.
In
Proceedings of the 10th International Conference: Learning and Intelligent Optimization (LION 10),
Vol. 10079,
pages 267--273,
Springer,
2016.
|
| Bischl/etal/2015a |
Bischl, Bernd and Lang, Michel and Mersmann, Olaf and Rahnenführer, Jörg and Weihs, Claus.
BatchJobs and BatchExperiments: Abstraction Mechanisms for Using R in Batch Environments.
In
Journal of Statistical Software,
Vol. 64,
No. 11,
pages 1--235,
2015.
|
| Kotthaus/2015a |
Kotthaus, Helena and Korb, Ingo and Marwedel, Peter.
Performance Analysis for Parallel R Programs: Towards Efficient Resource Utilization.
No. 1,
Department of Computer Science 12, TU Dortmund University,
2015.
|
| Kotthaus/etal/2015a |
Kotthaus, Helena and Korb, Ingo and Marwedel, Peter.
Distributed Performance Analysis for R.
In
R Implementation, Optimization and Tooling Workshop (RIOT),
Prag, Czech,
2015.
|
| Kotthaus/etal/2014a |
Kotthaus, Helena and Korb, Ingo and Lang, Michel and Bischl, Bernd and Rahnenführer, Jörg and Marwedel, Peter.
Runtime and Memory Consumption Analyses for Machine Learning R Programs.
In
Journal of Statistical Computation and Simulation,
Vol. 85,
No. 1,
pages 14-29,
2014.
|
| Kotthaus/etal/2014b |
Kotthaus, Helena and Korb, Ingo and Engel, Michael and Marwedel, Peter.
Dynamic Page Sharing Optimization for the R Language.
In
Proceedings of the 10th Symposium on Dynamic Languages,
pages 79-90,
Portland, Oregon, USA,
ACM,
2014.
|
| Kotthaus/etal/2014c |
Kotthaus, Helena and Korb, Ingo and Künne, Markus and Marwedel, Peter.
Performance Analysis for R: Towards a Faster R Interpreter.
In
Abstract Booklet of the International R User Conference (UseR!),
pages 104,
Los Angeles, USA,
2014.
|
| Lang/etal/2014a |
Lang, Michel and Kotthaus, Helena and Marwedel, Peter and Weihs, Claus and Rahnenführer, Jörg and Bischl, Bernd.
Automatic Model Selection for High-Dimensional Survival Analysis.
In
Journal of Statistical Computation and Simulation,
Vol. 85,
No. 1,
pages 62--76,
2014.
|
| Lee/etal/2014a |
Sangkyun Lee and Jörg Rahnenführer and Michel Lang and Katleen de Preter and Pieter Mestdagh and Jan Koster and Rogier Versteeg and Raymond Stallings and Luigi Varesio and Shahab Asgharzadeh and Johannes Schulte and Kathrin Fielitz and Melanie Heilmann and Katharina Morik and Alexander Schramm.
Robust Selection of Cancer Survival Signatures from High-Throughput Genomic Data Using Two-Fold Subsampling.
In
PLoS ONE,
Vol. 9,
pages e108818,
2014.
|
| Ahrens/etal/2013a |
Maike Ahrens and Michael Turewicz and Swaantje Casjens and Caroline May and Beate Pesch and Christian Stephan and Dirk Woitalla and Ralf Gold and Thomas Brüning and Helmut E. Meyer and Jörg Rahnenführer and Martin Eisenacher.
Detection of Patient Subgroups with Differential Expression in Omics Data: A Comprehensive Comparison of Univariate Measures.
In
PLoS ONE,
Vol. 8,
No. 11,
pages e79380,
2013.
|
| Cordes/etal/2013a |
Cordes, Daniel and Engel, Michael and Neugebauer, Olaf and Marwedel, Peter.
Automatic Extraction of Pipeline Parallelism for Embedded Heterogeneous Multi-Core Platforms.
In
Proceedings of the Sixteenth International Conference on Compilers, Architectures, and Synthesis for Embedded Systems (CASES 2013),
Montreal, Canada,
2013.
|
| Cordes/etal/2013b |
Cordes, Daniel and Engel, Michael and Neugebauer, Olaf and Marwedel, Peter.
Automatic Extraction of Multi-Objective Aware Parallelism for Heterogeneous MPSoCs.
In
Proceedings of the Sixth International Workshop on Multi-/Many-core Computing Systems (MuCoCoS 2013),
Edinburgh, Scotland, UK,
2013.
|
| Cordes/etal/2013c |
Cordes, Daniel and Engel, Michael and Neugebauer, Olaf and Marwedel, Peter.
Automatic Extraction of Task-Level Parallelism for Heterogeneous MPSoC.
In
Proceedings of the Fourth International Workshop on Parallel Software Tools and Tool Infrastructures (PSTI 2013),
Lyon, France,
2013.
|
| Kotthaus/etal/2013a |
Kotthaus, Helena and Lang, Michel and Rahnenführer, Jörg and Marwedel, Peter.
Runtime and Memory Consumption Analyses for Machine Learning R Programs.
In
Abstracts 45. Arbeitstagung, Ulmer Informatik-Berichte,
No. 2013-07,
pages 3--4,
Ulmer Informatik-Berichte,
2013.
|
| Lang/etal/2013a |
Lang, Michel and Bischl, Bernd and Weihs, Claus and Rahnenführer, Jörg.
Automatic model selection for high-dimensional survival analysis.
In
Abstracts der 45. Arbeitstagung,
No. 2013-07,
pages 32--33,
Ulmer Informatik-Berichte,
2013.
|
| Bischl/etal/2012a |
Bischl, Bernd and Lang, Michel and Mersmann, Olaf and Rahnenführer, Jörg and Weihs, Claus.
Computing on High Performance Clusters with R: Packages BatchJobs and BatchExperiments.
No. 1,
Fakultät Statistik, TU Dortmund,
2012.
|
| Kotthaus/etal/2012a |
Kotthaus, Helena and Plazar, Sascha and Marwedel, Peter.
A JVM-based Compiler Strategy for the R Language.
In
Abstract Booklet of the 8th International R User Conference (UseR!),
pages 68,
Nashville, Tennessee, USA,
2012.
|
| Lohr/etal/2012a |
Lohr, M. and Köllmann, C. and Freis, E. and Hellwig, B. and Hengstler, J. G. and Ickstadt, K. and Rahnenführer, J..
Optimal strategies for sequential validation of significant features from high-dimensional genomic data.
In
Journal of Toxicology and Environmental Health, Part A,
Vol. 75,
No. 8-10,
pages 447-460,
2012.
|
| Plazar/etal/2012a |
Plazar, Sascha and Falk, Heiko and Marwedel, Peter.
WCET-aware Static Locking of Instruction Caches.
In
Proceedings of the International Symposium on Code Generation and Optimization (CGO),
San Jose, CA, USA,
2012.
|
| Falk/etal/2011a |
Falk, Heiko and Kotthaus, Helena.
WCET-driven Cache-aware Code Positioning.
In
Proceedings of the International Conference on Compilers, Architectures and Synthesis for Embedded Systems (CASES),
pages 145-154,
Taipei, Taiwan,
2011.
|
| Kammers/etal/2011a |
Kammers, K. and Lang, M. and Hengstler, J. G. and Schmidt, M. and Rahnenführer, J..
Survival Models with Preclustered Gene Groups as Covariates.
In
BMC Bioinformatics,
Vol. 12,
No. 1,
pages 478,
2011.
|
| Plazar/etal/2011a |
Plazar, Sascha and Kleinsorge, Jan C. and Falk, Heiko and Marwedel, Peter.
WCET-driven Branch Prediction aware Code Positioning.
In
Proceedings of the International Conference on Compilers, Architectures and Synthesis for Embedded Systems (CASES),
pages 165-174,
Taipei, Taiwan,
2011.
|
| Lang/2019a |
Lang, Andreas.
Ablaufplanungsverfahren zur effizienten Ressourcennutzung bei der Algorithmenkonfiguration von maschinellen Lernverfahren.
TU Dortmund,
2018.
|
| Bommert/2016a |
Bommert, Andrea.
Stabile Variablenselektion in der Klassifikation.
2016.
|
| Lang/2016a |
Lang, Andreas.
Ressourcengewahre Ablaufplanungsverfahren für modellbasierte Optimierungen.
TU Dortmund,
2016.
|
| richter/2015a |
Jakob Richter.
Modellbasierte Hyperparameteroptimierung für maschinelle Lernverfahren auf großen Daten.
TU Dortmund,
2015.
|
| Kammers/Rahnenfuehrer/2010a |
Kammers, K. and Rahnenführer, J..
Improved Interpretability of Survival Models with Gene Groups as Covariates.
TU Dortmund, Department of Statistics,
2010.
|
| Lohr/etal/2010a |
Miriam Lohr AND Patricio Godoy AND Jan G Hengstler AND Jörg Rahnenführer AND Marco Grzegorczyk.
Extracting differential regulatory sub-networks from genome-wide microarray expression data.
In
Proceedings of the Seventh International Workshop on Computational Systems Biology (WCSB 2010),
Luxembourg,
2010.
|
| Plazar/etal/2010a |
Plazar, Sascha and Marwedel, Peter and Rahnenführer, Jörg.
Optimizing Execution Runtimes of R Programs.
In
Book of Abstracts of ISBIS-2010 (International Symposium on Business and Industrial Statistics),
Portorose, Slovenia,
2010.
|
| Alexa/2009a |
Adrian Alexa.
topGO: Enrichment analysis for Gene Ontology.
In
\urlhttp://www.bioconductor.org/packages/release/bioc/html/topGO.html,
2009.
|
| Lokuciejewski/etal/2009a |
Lokuciejewski, Paul and Gedikli, Fatih and Marwedel, Peter and Morik, Katharina.
Automatic WCET Reduction by Machine Learning Based Heuristics for Function Inlining.
In
SMART '09: Proc. of the 3rd Workshop on Statistical and Machine Learning Approaches to Architecture and Compilation,
pages 1--15,
Paphos / Cyprus,
2009.
|
| Podwojski/etal/2009a |
Katharina Podwojski and Arno Fritsch and Daniel C Chamrad and Wolfgang Paul and Barbara Sitek and Kai Stühler and Petra Mutzel and Christian Stephan and Helmut E Meyer and Wolfgang Urfer and Katja Ickstadt and Jörg Rahnenführer.
Retention time alignment algorithms for LC/MS data must consider non-linear shifts.
In
Bioinformatics,
Vol. 25,
No. 6,
pages 758--764,
Fakultät Statistik, Technische Universität Dortmund, 44221 Dortmund, Germany. katharina.podwojski@tu-dortmund.de,
2009.
|
| Bogojeska/etal/2008a |
Jasmina Bogojeska and Adrian Alexa and André Altmann and Thomas Lengauer and Jörg Rahnenführer.
Rtreemix: an R package for estimating evolutionary pathways and genetic progression scores.
In
Bioinformatics,
Vol. 24,
No. 20,
pages 2391--2392,
Max Planck Institute for Informatics, Saarbrücken, Germany. jasmina@mpi-inf.mpg.de,
2008.
|
| Plazar/etal/2008a |
Plazar, Sascha and Lokuciejewski, Paul and Marwedel, Peter.
A Retargetable Framework for Multi-objective WCET-aware High-level Compiler Optimizations.
In
Proceedings of The 29th IEEE Real-Time Systems Symposium (RTSS) WiP,
pages 49--52,
Barcelona / Spain,
2008.
|
| Alexa/etal/2006a |
Adrian Alexa and Jörg Rahnenführer and Thomas Lengauer.
Improved scoring of functional groups from gene expression data by decorrelating GO graph structure.
In
Bioinformatics,
Vol. 22,
No. 13,
pages 1600--1607,
Max-Planck-Institute for Informatics Stuhlsatzenhausweg 85, D-66123 Saarbrücken, Germany. alexa@mpi-sb.mpg.de,
2006.
|
| Falk/etal/2006b |
Falk, Heiko and Wagner, Jens and Schaefer, André.
Use of a Bit-true Data Flow Analysis for Processor-Specific Source Code Optimization.
In
4th IEEE Workshop on Embedded Systems for Real-Time Multimedia (ESTIMedia),
pages 133--138,
Seoul/Korea,
2006.
|
| Falk/Schwarzer/2006a |
Falk, Heiko and Schwarzer, Martin.
Loop Nest Splitting for WCET-Optimization and Predictability Improvement.
In
4th IEEE Workshop on Embedded Systems for Real-Time Multimedia (ESTIMedia),
pages 115--120,
Seoul/Korea,
2006.
|
| Yin/etal/2006a |
Junming Yin and Niko Beerenwinkel and Jörg Rahnenführer and Thomas Lengauer.
Model selection for mixtures of mutagenetic trees.
In
Stat Appl Genet Mol Biol,
Vol. 5,
pages Article17,
Department of EECS, University of California, Berkeley, CA, USA. junming@cs.berkeley.edu,
2006.
|
| Rahnenfuehrer/etal/2005a |
Jörg Rahnenführer and Niko Beerenwinkel and Wolfgang A Schulz and Christian Hartmann and Andreas von Deimling and Bernd Wullich and Thomas Lengauer.
Estimating cancer survival and clinical outcome based on genetic tumor progression scores.
In
Bioinformatics,
Vol. 21,
No. 10,
pages 2438--2446,
Max-Planck Institute for Informatics, Stuhlsatzenhausweg 85, D-66123 Saarbrücken, Germany. rahnenfj@mpi-sb.mpg.de,
2005.
|
