Vanschoren, Joaquin

36 publications

TMLR 2026 Unlocking [CLS] Features for Continual Post-Training Murat Onur Yildirim, Elif Ceren Gok Yildirim, Joaquin Vanschoren

ICLRW 2025 AutoML Benchmark with Shorter Time Constraints and Early Stopping Israel Campero Jurado, Pieter Gijsbers, Joaquin Vanschoren

NeurIPS 2025 CrypticBio: A Large Multimodal Dataset for Visually Confusing Species Georgiana Manolache, Gerard Schouten, Joaquin Vanschoren

ICLR 2025 Unsupervised Meta-Learning via In-Context Learning Anna Vettoruzzo, Lorenzo Braccaioli, Joaquin Vanschoren, Marlena Nowaczyk

JMLR 2024 AMLB: An AutoML Benchmark Pieter Gijsbers, Marcos L. P. Bueno, Stefan Coors, Erin LeDell, Sébastien Poirier, Janek Thomas, Bernd Bischl, Joaquin Vanschoren

JAIR 2024 Can Fairness Be Automated? Guidelines and Opportunities for Fairness-Aware AutoML Hilde J. P. Weerts, Florian Pfisterer, Matthias Feurer, Katharina Eggensperger, Edward Bergman, Noor H. Awad, Joaquin Vanschoren, Mykola Pechenizkiy, Bernd Bischl, Frank Hutter

CPAL 2024 Continual Learning with Dynamic Sparse Training: Exploring Algorithms for Effective Model Updates Murat Onur Yildirim, Elif Ceren Gok, Ghada Sokar, Decebal Constantin Mocanu, Joaquin Vanschoren

NeurIPS 2024 Croissant: A Metadata Format for ML-Ready Datasets Mubashara Akhtar, Omar Benjelloun, Costanza Conforti, Luca Foschini, Pieter Gijsbers, Joan Giner-Miguelez, Sujata Goswami, Nitisha Jain, Michalis Karamousadakis, Satyapriya Krishna, Michael Kuchnik, Sylvain Lesage, Quentin Lhoest, Pierre Marcenac, Manil Maskey, Peter Mattson, Luis Oala, Hamidah Oderinwale, Pierre Ruyssen, Tim Santos, Rajat Shinde, Elena Simperl, Arjun Suresh, Goeffry Thomas, Slava Tykhonov, Joaquin Vanschoren, Susheel Varma, Jos van der Velde, Steffen Vogler, Carole-Jean Wu, Luyao Zhang

DMLR 2024 DMLR: Data-Centric Machine Learning Research - Past, Present and Future Luis Oala, Manil Maskey, Lilith Bat-Leah, Alicia Parrish, Nezihe Merve Gürel, Tzu-Sheng Kuo, Yang Liu, Rotem Dror, Danilo Brajovic, Xiaozhe Yao, Max Bartolo, William A Gaviria Rojas, Ryan Hileman, Rainier Aliment, Michael W. Mahoney, Meg Risdal, Matthew Lease, Wojciech Samek, Debojyoti Dutta, Curtis G Northcutt, Cody Coleman, Braden Hancock, Bernard Koch, Girmaw Abebe Tadesse, Bojan Karlaš, Ahmed Alaa, Adji Bousso Dieng, Natasha Noy, Vijay Janapa Reddi, James Zou, Praveen Paritosh, Mihaela van der Schaar, Kurt Bollacker, Lora Aroyo, Ce Zhang, Joaquin Vanschoren, Isabelle Guyon, Peter Mattson

ECCV 2024 HyTAS: A Hyperspectral Image Transformer Architecture Search Benchmark and Analysis Fangqin Zhou, Mert Kilickaya, Joaquin Vanschoren, Ran Piao

CoLLAs 2024 Learning to Learn Without Forgetting Using Attention Anna Vettoruzzo, Joaquin Vanschoren, Mohamed-Rafik Bouguelia, Thorsteinn S. Rögnvaldsson

ICML 2024 MALIBO: Meta-Learning for Likelihood-Free Bayesian Optimization Jiarong Pan, Stefan Falkner, Felix Berkenkamp, Joaquin Vanschoren

ICML 2024 Position: TrustLLM: Trustworthiness in Large Language Models Yue Huang, Lichao Sun, Haoran Wang, Siyuan Wu, Qihui Zhang, Yuan Li, Chujie Gao, Yixin Huang, Wenhan Lyu, Yixuan Zhang, Xiner Li, Hanchi Sun, Zhengliang Liu, Yixin Liu, Yijue Wang, Zhikun Zhang, Bertie Vidgen, Bhavya Kailkhura, Caiming Xiong, Chaowei Xiao, Chunyuan Li, Eric P. Xing, Furong Huang, Hao Liu, Heng Ji, Hongyi Wang, Huan Zhang, Huaxiu Yao, Manolis Kellis, Marinka Zitnik, Meng Jiang, Mohit Bansal, James Zou, Jian Pei, Jian Liu, Jianfeng Gao, Jiawei Han, Jieyu Zhao, Jiliang Tang, Jindong Wang, Joaquin Vanschoren, John Mitchell, Kai Shu, Kaidi Xu, Kai-Wei Chang, Lifang He, Lifu Huang, Michael Backes, Neil Zhenqiang Gong, Philip S. Yu, Pin-Yu Chen, Quanquan Gu, Ran Xu, Rex Ying, Shuiwang Ji, Suman Jana, Tianlong Chen, Tianming Liu, Tianyi Zhou, William Yang Wang, Xiang Li, Xiangliang Zhang, Xiao Wang, Xing Xie, Xun Chen, Xuyu Wang, Yan Liu, Yanfang Ye, Yinzhi Cao, Yong Chen, Yue Zhao

MLJ 2024 Towards Efficient AutoML: A Pipeline Synthesis Approach Leveraging Pre-Trained Transformers for Multimodal Data Ambarish Moharil, Joaquin Vanschoren, Prabhant Singh, Damian A. Tamburri

NeurIPSW 2023 Applications of Optimal Transport Distances in Unsupervised AutoML Prabhant Singh, Joaquin Vanschoren

CVPRW 2023 Are Labels Needed for Incremental Instance Learning? Mert Kilickaya, Joaquin Vanschoren

IJCAI 2023 AutoML for Outlier Detection with Optimal Transport Distances Prabhant Singh, Joaquin Vanschoren

NeurIPS 2023 DataPerf: Benchmarks for Data-Centric AI Development Mark Mazumder, Colby Banbury, Xiaozhe Yao, Bojan Karlaš, William Gaviria Rojas, Sudnya Diamos, Greg Diamos, Lynn He, Alicia Parrish, Hannah Rose Kirk, Jessica Quaye, Charvi Rastogi, Douwe Kiela, David Jurado, David Kanter, Rafael Mosquera, Will Cukierski, Juan Ciro, Lora Aroyo, Bilge Acun, Lingjiao Chen, Mehul Raje, Max Bartolo, Evan Sabri Eyuboglu, Amirata Ghorbani, Emmett Goodman, Addison Howard, Oana Inel, Tariq Kane, Christine R. Kirkpatrick, D. Sculley, Tzu-Sheng Kuo, Jonas W Mueller, Tristan Thrush, Joaquin Vanschoren, Margaret Warren, Adina Williams, Serena Yeung, Newsha Ardalani, Praveen Paritosh, Ce Zhang, James Y Zou, Carole-Jean Wu, Cody Coleman, Andrew Y. Ng, Peter Mattson, Vijay Janapa Reddi

AutoML 2023 Neural Architecture Search for Visual Anomaly Segmentation Tommie Kerssies, Joaquin Vanschoren

MLJ 2023 Online AutoML: An Adaptive AutoML Framework for Online Learning Bilge Celik, Prabhant Singh, Joaquin Vanschoren

NeurIPSW 2022 LOTUS: Learning to Learn with Optimal Transport in Unsupervised Scenarios Prabhant Singh, Joaquin Vanschoren

NeurIPS 2022 Meta-Album: Multi-Domain Meta-Dataset for Few-Shot Image Classification Ihsan Ullah, Dustin Carrión-Ojeda, Sergio Escalera, Isabelle Guyon, Mike Huisman, Felix Mohr, Jan N. van Rijn, Haozhe Sun, Joaquin Vanschoren, Phan Anh Vu

NeurIPSW 2021 Open-Ended Learning Strategies for Learning Complex Locomotion Skills Fangqin Zhou, Joaquin Vanschoren

MLOSS 2021 OpenML-Python: An Extensible Python API for OpenML Matthias Feurer, Jan N. van Rijn, Arlind Kadra, Pieter Gijsbers, Neeratyoy Mallik, Sahithya Ravi, Andreas Müller, Joaquin Vanschoren, Frank Hutter

NeurIPSW 2021 Variational Task Encoders for Model-Agnostic Meta-Learning Luuk Schagen, Joaquin Vanschoren

ECML-PKDD 2020 GAMA: A General Automated Machine Learning Assistant Pieter Gijsbers, Joaquin Vanschoren

MLJ 2020 Guest Editors' Introduction to the Special Issue on Discovery Science Larisa N. Soldatova, Joaquin Vanschoren

ECML-PKDD 2019 Beyond Bag-of-Concepts: Vectors of Locally Aggregated Concepts Maarten Grootendorst, Joaquin Vanschoren

MLJ 2018 Meta-QSAR: A Large-Scale Application of Meta-Learning to Drug Design and Discovery Iván Olier, Noureddin Sadawi, G. Richard J. Bickerton, Joaquin Vanschoren, Crina Grosan, Larisa N. Soldatova, Ross D. King

MLJ 2018 Speeding up Algorithm Selection Using Average Ranking and Active Testing by Introducing Runtime Salisu Mamman Abdulrahman, Pavel Brazdil, Jan N. van Rijn, Joaquin Vanschoren

MLJ 2018 The Online Performance Estimation Framework: Heterogeneous Ensemble Learning for Data Streams Jan N. van Rijn, Geoffrey Holmes, Bernhard Pfahringer, Joaquin Vanschoren

ECML-PKDD 2013 OpenML: A Collaborative Science Platform Jan N. van Rijn, Bernd Bischl, Luís Torgo, Bo Gao, Venkatesh Umaashankar, Simon Fischer, Patrick Winter, Bernd Wiswedel, Michael R. Berthold, Joaquin Vanschoren

MLJ 2012 Experiment Databases - A New Way to Share, Organize and Learn from Experiments Joaquin Vanschoren, Hendrik Blockeel, Bernhard Pfahringer, Geoffrey Holmes

ECML-PKDD 2012 MDL-Based Analysis of Time Series at Multiple Time-Scales Ugo Vespier, Arno J. Knobbe, Siegfried Nijssen, Joaquin Vanschoren

ECML-PKDD 2012 Scientific Workflow Management with ADAMS Peter Reutemann, Joaquin Vanschoren

ECML-PKDD 2009 A Community-Based Platform for Machine Learning Experimentation Joaquin Vanschoren, Hendrik Blockeel