Joaquin Vanschoren

Research output

Content available in repository 2006 2015 2022 2023 2025

• 66 Conference contribution
• 38 Article
• 21 Chapter
• 10 Book editing
• 11 More
  • 3 Paper
  • 2 Foreword/editorial
  • 2 Other contribution
  • 2 Working paper
  • 1 Conference article
  • 1 Editorial

Content available in repository

Content available in repository

Search results

• 2024

  An Analysis of Evolutionary Migration Models for Multi-Objective, Multi-Fidelity AutoML

  Campero Jurado, I. (Corresponding author) & Vanschoren, J., 29 Jan 2024, 2023 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2023. Institute of Electrical and Electronics Engineers, p. 2940-2945 6 p. 10394059

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

  Open Access

  File

  • Multiobjective 100%
  • Automated Machine Learning 100%
  • Machine Learning 25%
  • Learning Framework 25%
  • Network Topology 25%
  4 Downloads (Pure)

• Continual Learning with Dynamic Sparse Training: Exploring Algorithms for Effective Model Updates

  Yildirim, M. O., Gok Yildirim, E. C., Sokar, G., Mocanu, D. C. & Vanschoren, J., 6 Jan 2024, Conference on Parsimony and Learning, 3-6 January 2024, Hongkong, China. Chi, Y., Dziugaite, G. K., Qu, Q., Wang Wang, A. & Zhu, Z. (eds.). PMLR, p. 94-107 14 p. (Proceedings of Machine Learning Research; vol. 234).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

  Open Access

  File

  • Sparsity 100%
  • Optimal Configuration 33%
  • Neural Network 33%
  • Regularization 33%
  7 Citations (Scopus)

  40 Downloads (Pure)

• Croissant: A Metadata Format for ML-Ready Datasets.

  Akhtar, M., Benjelloun, O., Conforti, C., Gijsbers, P., Giner-Miguelez, J., Jain, N., Kuchnik, M., Lhoest, Q., Marcenac, P., Maskey, M., Mattson, P., Oala, L., Ruyssen, P., Shinde, R., Simperl, E., Thomas, G., Tykhonov, S., Vanschoren, J., van der Velde, J. & Vogler, S. & 1 others, Wu, C.-J., 9 Jun 2024, DEEM '24: Proceedings of the Eighth Workshop on Data Management for End-to-End Machine Learning. Association for Computing Machinery, Inc., p. 1-6 6 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

  Open Access

  File

  • Metadata Format 100%
  • Machine Learning 100%
  • Learning System 100%
  • Learning Framework 20%
  • Critical Resource 20%
  18 Citations (Scopus)

  87 Downloads (Pure)

• MALIBO: Meta-learning for Likelihood-free Bayesian Optimization

  Pan, J., Falkner, S., Berkenkamp, F. & Vanschoren, J., 2024, International Conference on Machine Learning, 21-27 July 2024, Vienna, Austria. PMLR, p. 39102-39134 33 p. (Proceedings of Machine Learning Research; vol. 235).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

  Open Access

  File

  • Meta-Learning 100%
  • Task Uncertainty 20%
  6 Downloads (Pure)

• TRUSTLLM: Trustworthiness in Large Language Models

  Huang, Y. (Corresponding author), Sun, L., Wang, H., Wu, S., Zhang, Q., Li, Y., Gao, C., Huang, Y., Lyu, W., Zhang, Y., Li, X., Sun, H., Liu, Z., Liu, Y., Wang, Y., Zhang, Z., Vidgen, B., Kailkhura, B., Xiong, C. & Xiao, C. & 51 others, Li, C., Xing, E., Huang, F., Liu, H., Ji, H., Wang, H., Zhang, H., Yao, H., Kellis, M., Zitnik, M., Jiang, M., Bansal, M., Zou, J., Pei, J., Liu, J., Gao, J., Han, J., Zhao, J., Tang, J., Wang, J., Vanschoren, J., Mitchell, J. C., Shu, K., Xu, K., Chang, K. W., He, L., Huang, L., Backes, M., Gong, N. Z., Yu, P. S., Chen, P. Y., Gu, Q., Xu, R., Ying, R., Ji, S., Jana, S., Chen, T., Liu, T., Zhou, T., Wang, W., Li, X., Zhang, X., Wang, X., Xie, X., Chen, X., Wang, X., Liu, Y., Ye, Y., Cao, Y., Chen, Y. & Zhao, Y., 27 Jul 2024, Proceedings of the 41st International Conference on Machine Learning. Salakhutdinov, R., Kolter, Z., Heller, K., Weller, A., Oliver, N., Scarlett, J. & Berkenkamp, F. (eds.). PMLR, p. 20166-20270 105 p. (Proceedings of Machine Learning Research (PMLR); vol. 235).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

  Open Access

  File

  • Large Language Model 100%
  • Artificial Intelligence 100%
  • Open Source 30%
  • Future Direction 7%
  • Processing Capability 7%
  13 Citations (Scopus)

  261 Downloads (Pure)
• 2023

  AdaCL: Adaptive Continual Learning

  Yildirim, E. C. G., Yildirim, M. O., Kilickaya, M. & Vanschoren, J., 2023, Proceedings of the 1st ContinualAI Unconference, 2023. PMLR, p. 15-24 10 p. (Proceedings of Machine Learning Research; vol. 249).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

  Open Access

  File

  • Neural Network 100%
  • Bayesian Optimisation 100%
  • Adaptivity 100%
  4 Downloads (Pure)

• Are Labels Needed for Incremental Instance Learning?

  Kilickaya, M. & Vanschoren, J., 14 Aug 2023, 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2023. Institute of Electrical and Electronics Engineers, p. 2401-2409 9 p. 10208445

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

  Open Access

  File

  • Instance Learning 100%
  • Object Instance 100%
  • Learning Session 50%
  • Single Instance 50%
  3 Citations (Scopus)

• AutoML for Outlier Detection with Optimal Transport Distances

  Singh, P. & Vanschoren, J., 2023, Proceedings of the 32nd International Joint Conference on Artificial Intelligence, IJCAI 2023. Elkind, E. (ed.). International Joint Conferences on Artificial Intelligence (IJCAI), p. 7175-7178 4 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

  Open Access

  File

  • Outlier Detection 100%
  • Automated Machine Learning 100%
  • Data Distribution 40%
  • Underlying Distribution 20%
  6 Downloads (Pure)

• DataPerf: Benchmarks for Data-Centric AI Development

  Mazumder, M., Banbury, C., Yao, X., Karlaš, B., Rojas, W. G., Diamos, S., Diamos, G., He, L., Parrish, A., Kirk, H. R., Quaye, J., Rastogi, C., Kiela, D., Jurado, D., Kanter, D., Mosquera, R., Ciro, J., Aroyo, L., Acun, B. & Chen, L. & 24 others, Raje, M. S., Bartolo, M., Eyuboglu, S., Ghorbani, A., Goodman, E., Inel, O., Kane, T., Kirkpatrick, C. R., Kuo, T. S., Mueller, J., Thrush, T., Vanschoren, J., Warren, M., Williams, A., Yeung, S., Ardalani, N., Paritosh, P., Zhang, C., Zou, J., Wu, C. J., Coleman, C., Ng, A., Mattson, P. & Reddi, V. J., 2023, 37th Conference on Neural Information Processing Systems, NeurIPS 2023. Neural information processing systems foundation, 28 p. (Advances in Neural Information Processing Systems; vol. 36).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

  Open Access

  File

  • Baseline Implementation 100%
  17 Citations (Scopus)

  16 Downloads (Pure)

• Efficient-DASH: Automated Radar Neural Network Design Across Tasks and Datasets

  Boot, T., Cazin, N., Sanberg, W. & Vanschoren, J., 27 Jul 2023, 2023 IEEE Intelligent Vehicles Symposium, IV 2023. Institute of Electrical and Electronics Engineers, 7 p. 10186807

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

  Open Access

  File

  • Network Design 100%
  • Neural Network 100%
  • Neural Architecture Search 60%
  • Advanced Driver Assistance System 20%
  • Performance Gain 20%
  31 Downloads (Pure)

• Locality-Aware Hyperspectral Classification

  Zhou, F., Kilickaya, M. & Vanschoren, J., 2023, The 34th British Machine Vision Conference Proceedings. p. 22-24

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

  Open Access

  • Regularization Function 100%

• Neural Architecture Search for Visual Anomaly Segmentation

  Kerssies, T. & Vanschoren, J., 2023, Proceedings of the Second International Conference on Automated Machine Learning, AutoML 2023. Faust, A., Garnett, R., White, C., Hutter, F. & Gardner, J. R. (eds.). PMLR, 14 p. (Proceedings of Machine Learning Research; vol. 224).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

  Open Access

  File

  • Neural Architecture Search 100%
  • Computational Complexity 66%
  • Complex Task 33%
  • Segmentation Performance 33%
  • Validation Set 33%
  8 Downloads (Pure)

• NeurIPS’22 Cross-Domain MetaDL Challenge: Results and lessons learned

  Carrión-Ojeda, D., Alam, M., Escalera, S., Farahat, A., Ghosh, D., Diaz, T. G., Gupta, C., Guyon, I., Ky, J. R., Lee, X. Y., Liu, X., Mohr, F., Nguyen, M. H., Pintelas, E., Roth, S., Schaub-Meyer, S., Sun, H., Ullah, I., Vanschoren, J. & Vidyaratne, L. & 2 others, Wu, J. & Yin, X., 2023, Proceedings of the 36th Annual Conference on Neural Information Processing Systems, NeurIPS 2022. Ciccone, M., Stolovitzky, G. & Albrecht, J. (eds.). PMLR, p. 50-72 23 p. (Proceedings of Machine Learning Research; vol. 220).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

  Open Access

  File

  • Computational Resource 100%
  • Neural Network 100%
  • Deep Neural Network 50%
  • Substantial Amount 50%
  • Technical Aspect 50%
  1 Citation (Scopus)
• 2022

  Faster Performance Estimation for NAS with Embedding Proximity Score

  Franken, G., Singh, P. & Vanschoren, J., 2022, ECML/PKDD Workshop on Meta-Knowledge Transfer 2022. Brazdil, P., van Rijn, J. N., Gouk, H. & Mohr, F. (eds.). PMLR, p. 51-61 11 p. (Proceedings of Machine Learning Research (PMLR); vol. 191).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

  Open Access

  File

  • Estimation Performance 100%
  • Candidate Architecture 50%
  • Benchmarking 25%
  • Optimal Architecture 25%
  • Embedding Space 25%
  1 Citation (Scopus)

• Meta-Album: Multi-domain Meta-Dataset for Few-Shot Image Classification

  Ullah, I., Carrión-Ojeda, D., Escalera, S., Guyon, I., Huisman, M., Mohr, F., van Rijn, J. N., Sun, H., Vanschoren, J. & Vu, P. A., 2022, Advances in Neural Information Processing Systems 35 - 36th Conference on Neural Information Processing Systems, NeurIPS 2022. Koyejo, S., Mohamed, S., Agarwal, A., Belgrave, D., Cho, K. & Oh, A. (eds.). Neural information processing systems foundation, (Advances in Neural Information Processing Systems; vol. 35).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

  • Image Classification 100%
  • Meta Dataset 100%
  • Multidomain 100%
  • Transfer of Learning 100%
  • Learning Disabilities 100%
  21 Citations (Scopus)

• Multi-fidelity optimization method with asynchronous generalized island model for AutoML

  Campero Jurado, I. & Vanschoren, J., 19 Jul 2022, GECCO '22: Proceedings of the Genetic and Evolutionary Computation Conference Companion. Fieldsend, J. E. (ed.). New York: Association for Computing Machinery, Inc., p. 220-223 4 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

  Open Access

  File

  • Automated Machine Learning 100%
  • Field Research 16%
  • Machine Learning Technique 16%
  • Speed-up 16%
  • Optimization Technique 16%
  2 Citations (Scopus)

  2 Downloads (Pure)
• 2021

  Advances in MetaDL: AAAI 2021 challenge and workshop

  Baz, A. E., Guyon, I., Liu, Z., van Rijn, J. N., Treguer, S. & Vanschoren, J., 2021, 2021 AAAI Workshop on Meta-Learning and MetaDL Challenge. Guyon, I., van Rijn, J. N., Treguer, S. & Vanschoren, J. (eds.). PMLR, p. 1-16 16 p. (Proceedings of Machine Learning Research (PMLR); vol. 140).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

  Open Access

  File

  • Deep Learning Technique 100%
  • Trained Network 50%
  • Existing Architecture 50%
  • Solution Design 50%
  • Few-Shot Learning 50%
  4 Citations (Scopus)

• GAMA: A General Automated Machine Learning Assistant

  Gijsbers, P. (Corresponding author) & Vanschoren, J., 25 Feb 2021, Machine Learning and Knowledge Discovery in Databases. Applied Data Science and Demo Track: European Conference, ECML PKDD 2020, Ghent, Belgium, September 14–18, 2020, Proceedings, Part V. Dong, Y., Ifrim, G., Mladenić, D., Saunders, C. & Van Hoecke, S. (eds.). Cham: Springer, p. 560-564 5 p. (Lecture Notes in Computer Science (LNCS); vol. 12461)(Lecture Notes in Artificial Intelligence (LNAI); vol. 12461).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

  Open Access

  File

  • Automated Machine Learning 100%
  • Search Algorithm 22%
  • Postprocessing 11%
  • Machine Learning 11%
  • Benchmarking 11%
  21 Citations (Scopus)

  1 Downloads (Pure)

• Meta-learning for symbolic hyperparameter defaults

  Gijsbers, P., Pfisterer, F., van Rijn, J. N., Bischl, B. & Vanschoren, J., 8 Jul 2021, GECCO '21: Proceedings of the Genetic and Evolutionary Computation Conference Companion. Chicano, F. (ed.). New York: Association for Computing Machinery, Inc., p. 151-152 2 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

  Open Access

  File

  • Machine Learning Algorithm 100%
  • Machine Learning 50%
  • Performance Model 50%
  • Optimization Problem 50%
  • Optimal Algorithm 50%
  5 Citations (Scopus)

• OpenML Benchmarking Suites

  Bischl, B., Casalicchio, G., Feurer, M., Gijsbers, P., Hutter, F., Lang, M., Mantovani, R. G., Rijn, J. N. V. & Vanschoren, J., 2021, Proceedings of the NeurIPS 2021 Datasets and Benchmarks Track.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review
• 2020

  Beyond Bag-of-Concepts: Vectors of Locally Aggregated Concepts

  Grootendorst, M. & Vanschoren, J., 2020, Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2019, Proceedings. Brefeld, U., Fromont, E., Hotho, A., Knobbe, A., Maathuis, M. & Robardet, C. (eds.). Cham: Springer, p. 681-696 16 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11907 LNAI).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

  • Word Embedding 100%
  • Feature Vector 50%
  • Document Representation 16%
  • Representation Method 16%
  • Text Representation 16%
  5 Citations (Scopus)

• The ABC of data: A classifying framework for data readiness

  Castelijns, L. A., Maas, Y. & Vanschoren, J., 2020, Machine Learning and Knowledge Discovery in Databases - International Workshops of ECML PKDD 2019, Proceedings. Cellier, P. & Driessens, K. (eds.). Springer, p. 3-16 14 p. (Communications in Computer and Information Science; vol. 1167 CCIS).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

  Open Access

  File

  • Data Cleaning 100%
  • Machine Learning 50%
  • Automated Process 50%
  • Data Preprocessing 50%
  • Processing Step 50%
  9 Citations (Scopus)

  223 Downloads (Pure)
• 2018

  Data augmentation using conditional generative adversarial networks for leaf counting in arabidopsis plants

  Zhu, Y., Aoun, M., Krijn, M. P. C. M. & Vanschoren, J., Aug 2018, British Machine Vision Conference: Workshop on Computer Vision Problems in Plant Phenotyping. 11 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

  • Phenotype 100%
  • Conditioning 100%
  • Arabidopsis 100%
  • Generative Adversarial Networks 100%
  • Data Augmentation 100%
  1 Downloads (Pure)
• 2017

  Hyper-parameter tuning of a decision tree induction algorithm

  Mantovani, R. G., Horváth, T., Cerri, R., Vanschoren, J. & de Carvalho, A. C. P. L. F., 1 Feb 2017, 5th Brazilian Conference on Intelligent Systems, BRACIS 2016; Recife, Pernambuco; Brazil; 9 October 2016 through 12 October 2016. Piscataway: Institute of Electrical and Electronics Engineers, p. 37-42 6 p. 7839559

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

  • Decision Tree Induction 100%
  • Decision Tree Algorithm 100%
  • Process Optimization 50%
  • Machine Learning 50%
  • Parameter Value 50%
  78 Citations (Scopus)

  3 Downloads (Pure)

• Layered TPOT : speeding up tree-based pipeline optimization

  Gijsbers, P., Vanschoren, J. & Olson, R., 22 Sept 2017, Proceedings of the International Workshop on Automatic Selection, Configuration and Composition of Machine Learning Algorithms (AutoML 2017), 10 August 2017, Sydney, Australia: Collocated with ECMLPKDD 2017. Brazdil, P., Vanschoren, J., Hutter, F. & Hoos, H. (eds.). CEUR-WS.org, p. 49-68 20 p. (CEUR Workshop Proceedings; vol. 1998).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

  Open Access

  File

  • Machine Learning 100%
  • Large Data Set 100%
  • Genetic Programming 100%
  • Evolutionary Algorithms 100%
  • Automated Machine Learning 100%
  4 Citations (Scopus)

  172 Downloads (Pure)
• 2016

  Anticipating habit formation: a psychological computing approach to behavior change support

  Zhang, C., van Wissen, A., Lakens, D., Vanschoren, J., Ruyter, de, B. E. R. & IJsselsteijn, W. A., 2016, Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct. New York: Association for Computing Machinery, Inc., p. 1247-1254

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

  • Healthy Lifestyle 100%
  • Cognitive State 100%
  4 Citations (Scopus)

  2 Downloads (Pure)

• Having a blast : meta-learning and heterogeneous ensembles for data streams

  van Rijn, J. N., Holmes, G., Pfahringer, B. & Vanschoren, J., 7 Jan 2016, 15th IEEE International Conference on Data Mining (ICDM 2015), 14-17 November 2015, Atlantic City, New Jersey. Piscataway: Institute of Electrical and Electronics Engineers, p. 1003-1008 6 p. 7373426

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

  • Wide Range 100%
  • Data Mining 100%
  • Type Model 100%
  • Base Level 100%
  • Data Stream 100%
  40 Citations (Scopus)

  1 Downloads (Pure)

• Preface

  Festa, P., Sellmann, M. & Vanschoren, J., 2016, Learning and Intelligent Optimization: 10th International Conference, LION 10, Ischia, Italy, May 29 - June 1, 2016, Revised Selected Papers. Vanschoren, J. (ed.). Cham: Springer, p. V-VI (Lecture Notes in Computer Science (LNCS); vol. 10079).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review
• 2015

  Algorithm selection via meta-learning and sample-based active testing

  Abdulrahman, S. M., Brazdil, P., van Rijn, J. N. & Vanschoren, J., 2015, International Workshop on Meta-Learning and Algorithm Selection (MetaSel 2015, Porto, Portugal September 7, 2015; co-located with ECMLPKDD 2015). Vanschoren, J., Brazdil, P., Giraud-Carrier, C. & Kotthoff, L. (eds.). CEUR-WS.org, p. 55-66 (CEUR Workshop Proceedings; vol. 1455).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

  • Algorithm Selection 100%
  • Active Learning 25%
  • Ranking Algorithm 25%
  • Machine Learning Algorithm 25%
  • Experimental Result 25%
  10 Citations (Scopus)

  2 Downloads (Pure)

• Case study on bagging stable classifiers for data streams

  van Rijn, J. N., Holmes, G., Pfahringer, B. & Vanschoren, J., 2015, BENELEARN 2015. 6 p. (Computing and Mathematical Sciences Papers, University of Waikato.).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

  • Data Stream 100%
  • Case Study 100%
  • Base Classifier 50%
  • Data Mining Application 50%
  • Data Mining 50%

• Decreasing the false alarm rate of arrhythmias in intensive care using a machine learning approach

  Eerikäinen, L. M., Vanschoren, J., Rooijakkers, M. J., Vullings, R. & Aarts, R. M., 2015, 2015 Computing in Cardiology Conference (CinC), 6-9 September 2015, Nice, France. Piscataway: Institute of Electrical and Electronics Engineers, p. 293-296

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

  • Heart Arrhythmia 100%
  • Cross-Validation 16%
  • Heart Ventricle Arrhythmia 16%
  42 Citations (Scopus)

  6 Downloads (Pure)

• Effectiveness of random search in SVM hyper-parameter tuning

  Gomes Mantovani, R., Rossi, A. L. D., Vanschoren, J., Bischl, B. & de Carvalho, A. C. P. L. F., 2015, Neural Networks (IJCNN), 2015 International Joint Conference on. Institute of Electrical and Electronics Engineers, p. 1-8 8 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

  • Support Vector Machine 100%
  • Random Search 100%
  • Machine Learning 100%
  • Predictive Performance 50%
  • Grid Search 50%
  116 Citations (Scopus)

• Fast algorithm selection using learning curves

  Rijn, van, J. N., Abdulrahman, S. M., Brazdil, P. & Vanschoren, J., 2015, Advances in Intelligent Data Analysis XIV (14th International Symposium, IDA 2015, Saint Etienne, France, October 22-24, 2015). Fromont, E., De Bie, T. & Leeuwen, van, M. (eds.). Dordrecht: Springer, p. 298-309 (Lecture Notes in Computer Science; vol. 9385).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

  • Algorithm Selection 100%
  • Fast Algorithm 100%
  • Learning Curve 100%
  • Acceptable Solution 100%
  • Smaller Sample 100%
  52 Citations (Scopus)

  1 Downloads (Pure)

• Meta-learning recommendation of default hyper-parameter values for SVMs in classification tasks

  Gomes Mantovani, R., Rossi, A. L. D., Vanschoren, J. & Carvalho, A. C. P. L. F., 2015, International Workshop on Meta-Learning and Algorithm Selection (MetaSel 2015, Porto, Portugal September 7, 2015; co-located with ECMLPKDD 2015). Vanschoren, J., Brazdil, P., Giraud-Carrier, C. & Kotthoff, L. (eds.). CEUR-WS.org, p. 80-92 (CEUR Workshop Proceedings; vol. 1455).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

  • Parameter Value 100%
  • Support Vector Machine 100%
  • Predictive Performance 100%
  • Classification Task 100%
  • Optimization Technique 75%
  9 Citations (Scopus)

• OpenML : a networked science platform for machine learning

  Vanschoren, J., van Rijn, J. N., Bischl, B., Casalicchio, G., Lang, M. & Feurer, M., 2015, 2015 ICML Workshop on Machine Learning Open Source Software (MLOSS 2015), 10 Juli 2015, Lille, France. p. 1-3

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

  Open Access

  File
  314 Downloads (Pure)

• Sharing RapidMiner workflows and experiments with OpenML

  Rijn, van, J. N. & Vanschoren, J., 2015, International Workshop on Meta-Learning and Algorithm Selection (MetaSel 2015, Porto, Portugal September 7, 2015; co-located with ECMLPKDD 2015). Vanschoren, J., Brazdil, P., Giraud-Carrier, C. & Kotthoff, L. (eds.). CEUR-WS.org, p. 93-103 (CEUR Workshop Proceedings; vol. 1455).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

  • Machine Learning 100%
  • Rapidminer 100%
  • Learning Problem 50%
  • Graphical Interface 25%
  • Algorithm Selection 25%
  3 Citations (Scopus)

  1 Downloads (Pure)

• Taking machine learning research online with OpenML.

  Vanschoren, J., van Rijn, J. N. & Bischl, B., 2015, Proceedings of the 4th International Workshop on Big Data, Streams and Heterogeneous Source Mining: Algorithms, Systems, Programming Models and Applications. p. 1-4 4 p. (JMLR Workshop and Conference Proceedings; vol. 41).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

  Open Access

  File
  70 Downloads (Pure)

• To tune or not to tune : recommending when to adjust SVM hyper-parameters via Meta-learning

  Gomes Mantovani, R., Rossi, A. L. D., Vanschoren, J., Bischl, B. & Carvalho, A. C. P. L. F., 2015, 2015 International Joint Conference on Neural Networks (IJCNN), 12-17 July 2015, Killarney, Ireland . Piscataway: Institute of Electrical and Electronics Engineers, p. 1-8 8 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

  • Optimization Technique 100%
  • Support Vector Machine 100%
  • Classification Algorithm 100%
  • Process Optimization 100%
  • Predictive Performance 50%
  62 Citations (Scopus)

• Towards a collaborative platform for advanced meta-learning in healthcare predictive analytics

  Vukicevic, M., Radovanovic, S., Vanschoren, J., Napolitano, G. & Delibasic, B., 2015, International Workshop on Meta-Learning and Algorithm Selection (MetaSel 2015, Porto, Portugal September 7, 2015; co-located with ECMLPKDD 2015). Vanschoren, J., Brazdil, P., Giraud-Carrier, C. & Kotthoff, L. (eds.). CEUR-WS.org, p. 112-114 (CEUR Workshop Proceedings; vol. 1455).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

  • Learning 100%
  • Predictive Analytics 100%
  3 Downloads (Pure)

• Towards a data science collaboratory

  Vanschoren, J., Bischl, B., Hutter, F., Sebag, M., Kegl, B., Schmid, M., Napolitano, G., Wolstencroft, K., Williams, A. R. & Lawrence, N., 2015, Advances in Intelligent Data Analysis XIV: 14th International Symposium, IDA 2015, Saint Etienne. France, October 22 -24, 2015. Proceedings. Fromont, E., de Bie, T. & van Leeuwen, M. (eds.). Cham: Springer, p. XIX-XXI 3 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

  Open Access

  File
  1 Citation (Scopus)

  181 Downloads (Pure)

• Who is more positive in private? : analyzing sentiment differences across privacy levels and demographic factors in Facebook chats and posts

  Gao, B., Berendt, B. & Vanschoren, J., 2015, 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), 25-28 August 2015, Paris, France. Piscataway: Institute of Electrical and Electronics Engineers, p. 605-610 6 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

  • Chat 100%
  • Demographic Factor 100%
  • Facebook 100%
  • Attribute Value 50%
  • Detailed Insight 50%
  10 Citations (Scopus)
• 2014

  Algorithm selection on data streams

  Rijn, van, J. R., Holmes, G., Pfahringer, B. & Vanschoren, J., 2014, Discovery Science (17th International Conference, DS 2014, Bled, Slovenia, October 8-10, 2014. Proceedings). Dzeroski, S., Panov, P., Kocev, D. & Todorovski, L. (eds.). Heidelberg: Springer, p. 325-336 (Lecture Notes in Computer Science; vol. 8777).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

  • Data Stream 100%
  • Algorithm Selection 100%
  • Reproducibility 25%
  • Generalizability 25%
  • Data Characteristic 25%
  41 Citations (Scopus)

• Towards Meta-learning over Data Streams

  van Rijn, J. N., Holmes, G., Pfahringer, B. & Vanschoren, J., 2014, Meta-Learning and Algorithm Selection (MetaSel 2014, Prague, Czech Republic, August 19, 2014; co-located with ECAI 2014). Vanschoren, J., Soares, C. & Kotthoff, L. (eds.). CEUR-WS.org, p. 37-38 (CEUR Workshop Proceedings; vol. 1201).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

  • Meta-Learning 100%
  • Data Stream 100%
  1 Citation (Scopus)
• 2013

  A RapidMiner extension for open machine learning

  Van Rijn, J. N., Umaashankar, V., Fischer, S., Bischl, B., Torgo, L., Gao, B., Winter, P., Wiswedel, B., Berthold, M. R. & Vanschoren, J., 2013, RapidMiner Community Meeting and Conference. p. 59-70 12 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

  Open Access

• Modeling sensor dependencies between multiple sensor types

  Miao, S., Vespier, U., Vanschoren, J., Knobbe, A. & Cachucho, R., 2013, Proceedings of BeneLearn.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

  Open Access

• OpenML: A collaborative science platform

  van Rijn, J. N., Bischl, B., Torgo, L., Gao, B., Umaashankar, V., Fischer, S., Winter, P., Wiswedel, B., Berthold, M. R. & Vanschoren, J., 2013, Joint European Conference on Machine Learning and Knowledge Discovery in Databases. p. 645-649 5 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

  Open Access
  65 Citations (Scopus)
• 2012

  MDL-based analysis of time series at multiple time-scales

  Vespier, U., Knobbe, A., Nijssen, S. & Vanschoren, J., 2012, Joint European Conference on Machine Learning and Knowledge Discovery in Databases. p. 371-386 16 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

  Open Access
  13 Citations (Scopus)

• MDL-based identification of relevant temporal scales in time series

  Vespier, U., Knobbe, A., Nijssen, S. & Vanschoren, J., 2012, Fifth workshop on Information Theoretic Methods in Science and Engineering (WITMSE-2012), 27-30 August 2012, Amsterdam, The Netherlands . p. 64 1 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

  Open Access

• Scientific workflow management with ADAMS

  Reutemann, P. & Vanschoren, J., 2012, Joint European Conference on Machine Learning and Knowledge Discovery in Databases. p. 833-837 5 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review
  10 Citations (Scopus)

• Selecting classification algorithms with active testing

  Leite, R., Brazdil, P. & Vanschoren, J., 2012, International Workshop on Machine Learning and Data Mining in Pattern Recognition. p. 117-131 15 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review
  72 Citations (Scopus)