Lars Kotthoff

发表

Automated Machine Learning: Methods, Systems, Challenges

Lars Kotthoff, Joaquin Vanschoren, Frank Hutter, 2019, The Springer Series on Challenges in Machine Learning.

Machine-learning-assisted fabrication: Bayesian optimization of laser-induced graphene patterning using in-situ Raman analysis

Lars Kotthoff, V. Jain, H. Wahab, 2020, Carbon.

AI for Materials Science: Tuning Laser-Induced Graphene Production and Beyond

Lars Kotthoff, V. Jain, H. Wahab, 2019 .

Leveraging TSP Solver Complementarity through Machine Learning

Heike Trautmann, Jakob Bossek, Lars Kotthoff, 2018, Evolutionary Computation.

I have 10 ways of solving this problem and no idea which is best! An introduction to algorithm selection and configuration

Lars Kotthoff, Lars Kotthoff, 2014 .

Machine-learning-assisted fabrication: Bayesian optimization of laser-induced graphene patterning using in-situ Raman analysis

Lars Kotthoff, V. Jain, H. Wahab, 2020, Carbon.

How explainable are adversarially-robust CNNs?

Anh M Nguyen, Lars Kotthoff, Peijie Chen, 2022, ArXiv.

AutoML 2016 Workshop Proceedings : Proceedings of the Workshop on Automatic Machine Learning, 24 June 2016, New York, New York, USA

Lars Kotthoff, Joaquin Vanschoren, Frank Hutter, 2016 .

The Inductive Constraint Programming Loop: Extended Abstract

Luc De Raedt, Barry O'Sullivan, Dino Pedreschi, 2016 .

FlexiBO: A Decoupled Cost-Aware Multi-Objective Optimization Approach for Deep Neural Networks

Md Shahriar Iqbal, Pooyan Jamshidi, Lars Kotthoff, 2020, J. Artif. Intell. Res..

Getting the Best Bang For Your Buck: Choosing What to Evaluate for Faster Bayesian Optimization

Md Shahriar Iqbal, Pooyan Jamshidi, Lars Kotthoff, 2022 .

Engineering the Policy-making Life Cycle Seventh Framework Programme – Grant Agreement 288147 Deliverable 5 . 2 Prototype of incentive policy mechanism Document type : Deliverable Dissemination Level : Public

S. D. Givry, H. Simonis, Lars Kotthoff, 2013 .

A Machine Learning Technique to Predict Biaxial Failure Envelope of Unidirectional Composite Lamina

Lars Kotthoff, R. Fertig, Ray S. FERTIG, III, 2018, American Society for Composites 2018.

Optimizing Laser-Induced Graphene Production

Lars Kotthoff, H. Wahab, Alexander Tyrrell, 2022, PAIS@ECAI.

Machine Learning in R [R package mlr version 2.18.0]

Bernd Bischl, Lars Kotthoff, Patrick Schratz, 2020 .

International Workshop on Meta-Learning and Algorithm Selection (MetaSel 2015, Porto, Portugal September 7, 2015; co-located with ECMLPKDD 2015)

Lars Kotthoff, Joaquin Vanschoren, Pavel Brazdil, 2015 .

An evaluation of machine learning in algorithm selection for search problems

Lars Kotthoff, Ian P. Gent, Ian Miguel, 2012, AI Commun..

A Preliminary Evaluation of Machine Learning in Algorithm Selection for Search Problems

Lars Kotthoff, Ian P. Gent, Ian Miguel, 2011, SOCS.

Using the Shapley Value to Analyze Algorithm Portfolios

Talal Rahwan, Tomasz P. Michalak, Lars Kotthoff, 2016, AAAI.

On Algorithm Selection, with an application to combinatorial search problems

Lars Kotthoff, Lars Kotthoff, 2015, Constraints.

Bayesian Optimization in Materials Science: A Survey pdf

Lars Kotthoff, Hud Wahab, Patrick Johnson, 2021, ArXiv.

LLAMA: Leveraging Learning to Automatically Manage Algorithms pdf

Lars Kotthoff, Lars Kotthoff, 2013, ArXiv.

mlr: Machine Learning in R

Bernd Bischl, Michel Lang, Lars Kotthoff, 2016, J. Mach. Learn. Res..

Auto-WEKA 2.0: Automatic model selection and hyperparameter optimization in WEKA

Lars Kotthoff, Kevin Leyton-Brown, Holger H. Hoos, 2017, J. Mach. Learn. Res..

Machine Learning in R

Bernd Bischl, Michel Lang, Jakob Bossek, 2015 .

Opening the Black Box: Automated Software Analysis for Algorithm Selection

H. Hoos, Lars Kotthoff, Marie Anastacio, 2022, AutoML.

The algorithm selection competitions 2015 and 2017

Lars Kotthoff, Marius Lindauer, Jan N. van Rijn, 2018, Artif. Intell..

A Regression-Based Methodology for Online Algorithm Selection

Bernd Bischl, Hans Degroote, Lars Kotthoff, 2018, SOCS.

ASlib: A benchmark library for algorithm selection

Bernd Bischl, Marius Thomas Lindauer, Lars Kotthoff, 2015, Artif. Intell..

Reinforcement Learning for Automatic Online Algorithm Selection - an Empirical Study

Bernd Bischl, Hans Degroote, Lars Kotthoff, 2016, ITAT.

Improving the State of the Art in Inexact TSP Solving Using Per-Instance Algorithm Selection

Heike Trautmann, Lars Kotthoff, Pascal Kerschke, 2015, LION.

META-LEARNING AND ALGORITHM SELECTION WORKSHOP AT ECAI 2014

Lars Kotthoff, Joaquin Vanschoren, Carlos Soares, 2014 .

Algorithm Selection for Combinatorial Search Problems: A Survey pdf

Lars Kotthoff, Lars Kotthoff, 2012, AI Mag..

Learning When to Use Lazy Learning in Constraint Solving

Lars Kotthoff, Ian P. Gent, Ian Miguel, 2010, ECAI.

Portfolios of Subgraph Isomorphism Algorithms

Christine Solnon, Lars Kotthoff, Ciaran McCreesh, 2016, LION.

Bio-like Composite Microstructure Designs for Enhanced Damage Tolerance via Machine Learning

Lars Kotthoff, Sarah Hankins, Ray S. Fertig, 2019, American Society for Composites 2019.

An automated approach to generating efficient constraint solvers

Lars Kotthoff, Ian Miguel, Dharini Balasubramaniam, 2012, 2012 34th International Conference on Software Engineering (ICSE).

mlr3: A modern object-oriented machine learning framework in R

Bernd Bischl, Lars Kotthoff, Patrick Schratz, 2019, J. Open Source Softw..

The Inductive Constraint Programming Loop

Luc De Raedt, Barry O'Sullivan, Dino Pedreschi, 2015, IEEE Intelligent Systems.

Is Algorithm Selection Worth It? Comparing Selecting Single Algorithms and Parallel Execution

Lars Kotthoff, Haniye Kashgarani, 2021, MetaDL@AAAI.

The Exact Closest String Problem as a Constraint Satisfaction Problem pdf

Lars Kotthoff, Tom Kelsey, Lars Kotthoff, 2010, ArXiv.

Exact Closest String as a Constraint Satisfaction Problem

Lars Kotthoff, Tom Kelsey, Lars Kotthoff, 2011, ICCS.

Automated Machine Learning: Methods, Systems, Challenges

Berna Bakir Batu, F. Hutter, J. Vanschoren, 2019, The Springer Series on Challenges in Machine Learning.

Reliability of computational experiments on virtualised hardware

Lars Kotthoff, Lars Kotthoff, 2011, J. Exp. Theor. Artif. Intell..

ICON Loop Health Show Case

Barry O'Sullivan, Barry Hurley, Lars Kotthoff, 2016, Data Mining and Constraint Programming.

Find Your Way Back: Mobility Profile Mining with Constraints

Barry O'Sullivan, Lars Kotthoff, Riccardo Guidotti, 2015, CP.

Data Mining and Constraint Programming

Luc De Raedt, Barry O'Sullivan, Dino Pedreschi, 2016, Lecture Notes in Computer Science.

Advanced Portfolio Techniques

Barry O'Sullivan, Barry Hurley, Lars Kotthoff, 2016, Data Mining and Constraint Programming.

Case Studies and Challenges in Reproducibility in the Computational Sciences

Lars Kotthoff, Miguel A. Nacenta, Ciaran McCreesh, 2014, 1408.2123.

Proteus: A Hierarchical Portfolio of Solvers and Transformations pdf

Barry O'Sullivan, Barry Hurley, Lars Kotthoff, 2013, CPAIOR.

FlexiBO: Cost-Aware Multi-Objective Optimization of Deep Neural Networks pdf

Lars Kotthoff, Pooyan Jamshidi, Jianhai Su, 2020, ArXiv.

The ICON Challenge on Algorithm Selection

Barry O'Sullivan, Barry Hurley, Lars Kotthoff, 2015, AI Mag..

How explainable are adversarially-robust CNNs?

Anh M Nguyen, Lars Kotthoff, Peijie Chen, 2022, ArXiv.

Qualitative modelling via constraint programming pdf

Lars Kotthoff, Ian P. Gent, Ian Miguel, 2012, Constraints.

Automated Symmetry Breaking and Model Selection in Conjure

Bilal Syed Hussain, Lars Kotthoff, Ian P. Gent, 2013, CP.

Quantifying Algorithmic Improvements over Time

Talal Rahwan, Tomasz P. Michalak, Lars Kotthoff, 2018, IJCAI.

Automated Benchmark-Driven Design and Explanation of Hyperparameter Optimizers pdf

Lars Kotthoff, Florian Pfisterer, Michel Lang, 2021, IEEE Transactions on Evolutionary Computation.

Transfer Learning for Performance Modeling of Deep Neural Network Systems pdf

Lars Kotthoff, Pooyan Jamshidi, Md Shahriar Iqbal, 2019, OpML.

Hybrid Regression-Classification Models for Algorithm Selection

Lars Kotthoff, Lars Kotthoff, 2012, ECAI.

Ensemble Classification for Constraint Solver Configuration

Lars Kotthoff, Ian Miguel, Peter Nightingale, 2010, CP.

Machine learning for constraint solver design -- A case study for the alldifferent constraint pdf

Lars Kotthoff, Ian P. Gent, Ian Miguel, 2010, ArXiv.

Web-Scale Distributed eScience AI Search across Disconnected and Heterogeneous Infrastructures

Lars Kotthoff, Tom Kelsey, Martin McCaffery, 2014, 2014 IEEE 10th International Conference on e-Science.

A framework for large-scale distributed AI search across disconnected heterogeneous infrastructures pdf

Lars Kotthoff, Tom Kelsey, Martin McCaffery, 2012, ArXiv.

Distributed solving through model splitting pdf

Lars Kotthoff, Neil C. A. Moore, Lars Kotthoff, 2010, ArXiv.

Web-scale distributed AI search across disconnected and heterogeneous infrastructures

Lars Kotthoff, T. Kelsey, M. McCaffery, 2014 .

ICON Loop Carpooling Show Case

Barry O'Sullivan, Dino Pedreschi, Lars Kotthoff, 2016, Data Mining and Constraint Programming.

mlr3pipelines - Flexible Machine Learning Pipelines in R

B. Bischl, Lars Kotthoff, Michel Lang, 2021, J. Mach. Learn. Res..

Auto-WEKA 2.0: Automatic model selection and hyperparameter optimization in WEKA

F. Hutter, C. Thornton, H. Hoos, 2017, J. Mach. Learn. Res..