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2020 – today
- 2024
[j45]Manh Hung Nguyen
, Lisheng Sun-Hosoya, Isabelle Guyon:
Meta-learning from learning curves for budget-limited algorithm selection. Pattern Recognit. Lett. 185: 225-231 (2024)- [c110]Haocheng Yuan, Ajian Liu, Junze Zheng, Jun Wan, Jiankang Deng, Sergio Escalera, Hugo Jair Escalante, Isabelle Guyon, Zhen Lei:
Unified Physical-Digital Attack Detection Challenge. CVPR Workshops 2024: 919-929 - [c109]Birhanu Hailu Belay, Isabelle Guyon, Tadele Mengiste, Bezawork Tilahun, Marcus Liwicki, Tesfa Tegegne, Romain Egele:
A Historical Handwritten Dataset for Ethiopic OCR with Baseline Models and Human-Level Performance. ICDAR (3) 2024: 23-38 - [i45]Hugo Jair Escalante Balderas, Isabelle Guyon, Addison Howard, Walter Reade, Sébastien Treguer:
Challenge design roadmap. CoRR abs/2401.13693 (2024) - [i44]Haocheng Yuan, Ajian Liu, Junze Zheng, Jun Wan, Jiankang Deng, Sergio Escalera, Hugo Jair Escalante, Isabelle Guyon, Zhen Lei:
Unified Physical-Digital Attack Detection Challenge. CoRR abs/2404.06211 (2024) - [i43]Romain Egele, Júlio C. S. Jacques Júnior, Jan N. van Rijn, Isabelle Guyon, Xavier Baró, Albert Clapés, Prasanna Balaprakash, Sergio Escalera, Thomas B. Moeslund, Jun Wan:
AI Competitions and Benchmarks: Dataset Development. CoRR abs/2404.09703 (2024) - [i42]Eleni Triantafillou, Peter Kairouz, Fabian Pedregosa, Jamie Hayes, Meghdad Kurmanji, Kairan Zhao, Vincent Dumoulin, Júlio C. S. Jacques Júnior, Ioannis Mitliagkas, Jun Wan, Lisheng Sun-Hosoya, Sergio Escalera, Gintare Karolina Dziugaite, Peter Triantafillou, Isabelle Guyon:
Are we making progress in unlearning? Findings from the first NeurIPS unlearning competition. CoRR abs/2406.09073 (2024) - 2023
- [j44]Sabrina Amrouche, Laurent Basara, Paolo Calafiura, Dmitry Emeliyanov, Victor Estrade, Steven Farrell, Cécile Germain, Vladimir Vava Gligorov, Tobias Golling, Sergey Gorbunov, Heather M. Gray, Isabelle Guyon, Mikhail Hushchyn, Vincenzo Innocente, Moritz Kiehn, Marcel Kunze, Edward Moyse, David Rousseau, Andreas Salzburger, Andrey Ustyuzhanin, Jean-Roch Vlimant:
The Tracking Machine Learning Challenge: Throughput Phase. Comput. Softw. Big Sci. 7(1): 1 (2023) - [j43]Adrien Pavao, Isabelle Guyon, Anne-Catherine Letournel, Dinh-Tuan Tran, Xavier Baró, Hugo Jair Escalante, Sergio Escalera, Tyler Thomas, Zhen Xu:
CodaLab Competitions: An Open Source Platform to Organize Scientific Challenges. J. Mach. Learn. Res. 24: 198:1-198:6 (2023) - [c108]Romain Égelé, Isabelle Guyon, Venkatram Vishwanath, Prasanna Balaprakash:
Asynchronous Decentralized Bayesian Optimization for Large Scale Hyperparameter Optimization. e-Science 2023: 1-10 - [c107]Romain Egele, Isabelle Guyon, Yixuan Sun, Prasanna Balaprakash:
Is One Epoch All You Need For Multi-Fidelity Hyperparameter Optimization? ESANN 2023 - [c106]Haozhe Sun, Isabelle Guyon, Felix Mohr, Hedi Tabia:
RRR-Net: Reusing, Reducing, and Recycling a Deep Backbone Network. IJCNN 2023: 1-9 - [i41]Ihsan Ullah, Dustin Carrión-Ojeda, Sergio Escalera, Isabelle Guyon, Mike Huisman, Felix Mohr, Jan N. van Rijn, Haozhe Sun, Joaquin Vanschoren, Phan Anh Vu:
Meta-Album: Multi-domain Meta-Dataset for Few-Shot Image Classification. CoRR abs/2302.08909 (2023) - [i40]Romain Egele, Isabelle Guyon, Yixuan Sun, Prasanna Balaprakash:
Is One Epoch All You Need For Multi-Fidelity Hyperparameter Optimization? CoRR abs/2307.15422 (2023) - [i39]Haozhe Sun, Isabelle Guyon:
Modularity in Deep Learning: A Survey. CoRR abs/2310.01154 (2023) - [i38]Haozhe Sun, Isabelle Guyon, Felix Mohr, Hedi Tabia:
RRR-Net: Reusing, Reducing, and Recycling a Deep Backbone Network. CoRR abs/2310.01157 (2023) - [i37]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 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 Karlas, Ahmed M. Alaa, Adji Bousso Dieng, Natasha F. Noy, Vijay Janapa Reddi, James Zou, Praveen K. Paritosh, Mihaela van der Schaar, Kurt D. Bollacker, Lora Aroyo, Ce Zhang, Joaquin Vanschoren, Isabelle Guyon, Peter Mattson:
DMLR: Data-centric Machine Learning Research - Past, Present and Future. CoRR abs/2311.13028 (2023) - 2022
- [j42]Joseph Pedersen, Rafael Muñoz-Gómez, Jiangnan Huang, Haozhe Sun, Wei-Wei Tu, Isabelle Guyon:
LTU Attacker for Membership Inference. Algorithms 15(7): 254 (2022) - [j41]Zhen Xu, Lanning Wei, Huan Zhao, Rex Ying, Quanming Yao, Wei-Wei Tu, Isabelle Guyon:
Bridging the Gap of AutoGraph Between Academia and Industry: Analyzing AutoGraph Challenge at KDD Cup 2020. Frontiers Artif. Intell. 5 (2022) - [j40]Karan Bhanot, Joseph Pedersen, Isabelle Guyon, Kristin P. Bennett:
Investigating synthetic medical time-series resemblance. Neurocomputing 494: 368-378 (2022) - [j39]Diviyan Kalainathan, Olivier Goudet, Isabelle Guyon, David Lopez-Paz, Michèle Sebag:
Structural Agnostic Modeling: Adversarial Learning of Causal Graphs. J. Mach. Learn. Res. 23: 219:1-219:62 (2022) - [j38]Zhen Xu, Sergio Escalera, Adrien Pavão, Magali Richard, Wei-Wei Tu, Quanming Yao, Huan Zhao, Isabelle Guyon:
Codabench: Flexible, easy-to-use, and reproducible meta-benchmark platform. Patterns 3(7): 100543 (2022) - [j37]Júlio C. S. Jacques Júnior, Yagmur Güçlütürk, Marc Pérez, Umut Güçlü, Carlos Andújar, Xavier Baró, Hugo Jair Escalante, Isabelle Guyon, Marcel A. J. van Gerven, Rob van Lier, Sergio Escalera:
First Impressions: A Survey on Vision-Based Apparent Personality Trait Analysis. IEEE Trans. Affect. Comput. 13(1): 75-95 (2022) - [j36]Hugo Jair Escalante, Heysem Kaya, Albert Ali Salah, Sergio Escalera, Yagmur Güçlütürk, Umut Güçlü, Xavier Baró, Isabelle Guyon, Júlio C. S. Jacques Júnior, Meysam Madadi, Stéphane Ayache, Evelyne Viegas, Furkan Gürpinar, Achmadnoer Sukma Wicaksana, Cynthia C. S. Liem, Marcel A. J. van Gerven, Rob van Lier:
Modeling, Recognizing, and Explaining Apparent Personality From Videos. IEEE Trans. Affect. Comput. 13(2): 894-911 (2022) - [j35]Jun Wan, Chi Lin, Longyin Wen, Yunan Li, Qiguang Miao, Sergio Escalera, Gholamreza Anbarjafari, Isabelle Guyon, Guodong Guo, Stan Z. Li:
ChaLearn Looking at People: IsoGD and ConGD Large-Scale RGB-D Gesture Recognition. IEEE Trans. Cybern. 52(5): 3422-3433 (2022) - [c105]Dustin Carrión-Ojeda, Hong Chen, Adrian El Baz, Sergio Escalera, Chaoyu Guan, Isabelle Guyon, Ihsan Ullah, Xin Wang, Wenwu Zhu:
NeurIPS’22 Cross-Domain MetaDL competition: Design and baseline results. Meta-Knowledge Transfer @ ECML/PKDD 2022: 24-37 - [c104]Adrien Pavão, Isabelle Guyon, Zhengying Liu:
Filtering participants improves generalization in competitions and benchmarks. ESANN 2022 - [c103]Romain Egele, Romit Maulik, Krishnan Raghavan, Bethany Lusch, Isabelle Guyon, Prasanna Balaprakash:
AutoDEUQ: Automated Deep Ensemble with Uncertainty Quantification. ICPR 2022: 1908-1914 - [c102]Manh Hung Nguyen, Lisheng Sun-Hosoya, Nathan Grinsztajn, Isabelle Guyon:
Meta-learning from Learning Curves: Challenge Design and Baseline Results. IJCNN 2022: 1-8 - [c101]Ihsan Ullah, Dustin Carrión-Ojeda, Sergio Escalera, Isabelle Guyon, Mike Huisman, Felix Mohr, Jan N. van Rijn, Haozhe Sun, Joaquin Vanschoren, Phan Anh Vu:
Meta-Album: Multi-domain Meta-Dataset for Few-Shot Image Classification. NeurIPS 2022 - [e14]Isabelle Guyon, Marius Lindauer, Mihaela van der Schaar, Frank Hutter, Roman Garnett:
International Conference on Automated Machine Learning, AutoML 2022, 25-27 July 2022, Johns Hopkins University, Baltimore, MD, USA. Proceedings of Machine Learning Research 188, PMLR 2022 [contents] - [i36]Zhengying Liu, Adrien Pavao, Zhen Xu, Sergio Escalera, Fabio Ferreira, Isabelle Guyon, Sirui Hong, Frank Hutter, Rongrong Ji, Júlio C. S. Jacques Júnior, Ge Li, Marius Lindauer, Zhipeng Luo, Meysam Madadi, Thomas Nierhoff, Kangning Niu, Chunguang Pan, Danny Stoll, Sébastien Treguer, Jin Wang, Peng Wang, Chenglin Wu, Youcheng Xiong, Arber Zela, Yang Zhang:
Winning solutions and post-challenge analyses of the ChaLearn AutoDL challenge 2019. CoRR abs/2201.03801 (2022) - [i35]Haozhe Sun, Wei-Wei Tu, Isabelle Guyon:
OmniPrint: A Configurable Printed Character Synthesizer. CoRR abs/2201.06648 (2022) - [i34]Adrian El Baz, Isabelle Guyon, Zhengying Liu, Jan N. van Rijn, Sébastien Treguer, Joaquin Vanschoren:
Advances in MetaDL: AAAI 2021 challenge and workshop. CoRR abs/2202.01890 (2022) - [i33]Joseph Pedersen, Rafael Muñoz-Gómez, Jiangnan Huang, Haozhe Sun, Wei-Wei Tu, Isabelle Guyon:
LTU Attacker for Membership Inference. CoRR abs/2202.02278 (2022) - [i32]Sebastian Weichwald, Søren Wengel Mogensen, Tabitha Edith Lee, Dominik Baumann, Oliver Kroemer, Isabelle Guyon, Sebastian Trimpe, Jonas Peters, Niklas Pfister:
Learning by Doing: Controlling a Dynamical System using Causality, Control, and Reinforcement Learning. CoRR abs/2202.06052 (2022) - [i31]Germán Barquero, Johnny Núñez, Sergio Escalera, Zhen Xu, Wei-Wei Tu, Isabelle Guyon, Cristina Palmero:
Didn't see that coming: a survey on non-verbal social human behavior forecasting. CoRR abs/2203.02480 (2022) - [i30]Germán Barquero, Johnny Núñez, Zhen Xu, Sergio Escalera, Wei-Wei Tu, Isabelle Guyon, Cristina Palmero:
Comparison of Spatio-Temporal Models for Human Motion and Pose Forecasting in Face-to-Face Interaction Scenarios. CoRR abs/2203.03245 (2022) - [i29]Zhen Xu, Lanning Wei, Huan Zhao, Rex Ying, Quanming Yao, Wei-Wei Tu, Isabelle Guyon:
Bridging the Gap of AutoGraph between Academia and Industry: Analysing AutoGraph Challenge at KDD Cup 2020. CoRR abs/2204.02625 (2022) - [i28]Adrian El Baz, André C. P. L. F. de Carvalho, Hong Chen, Fabio Ferreira, Henry Gouk, Shell Hu, Frank Hutter, Zhengying Liu, Felix Mohr, Jan N. van Rijn, Xin Wang, Isabelle Guyon:
Lessons learned from the NeurIPS 2021 MetaDL challenge: Backbone fine-tuning without episodic meta-learning dominates for few-shot learning image classification. CoRR abs/2206.08138 (2022) - [i27]Romain Egele, Joceran Gouneau, Venkatram Vishwanath, Isabelle Guyon, Prasanna Balaprakash:
Asynchronous Distributed Bayesian Optimization at HPC Scale. CoRR abs/2207.00479 (2022) - [i26]Gaëtan Serré, Eva Boguslawski, Benjamin Donnot, Adrien Pavão, Isabelle Guyon, Antoine Marot:
Reinforcement learning for Energies of the future and carbon neutrality: a Challenge Design. CoRR abs/2207.10330 (2022) - [i25]Manh Hung Nguyen, Lisheng Sun, Nathan Grinsztajn, Isabelle Guyon:
Meta-learning from Learning Curves Challenge: Lessons learned from the First Round and Design of the Second Round. CoRR abs/2208.02821 (2022) - [i24]Dustin Carrión-Ojeda, Hong Chen, Adrian El Baz, Sergio Escalera, Chaoyu Guan, Isabelle Guyon, Ihsan Ullah, Xin Wang, Wenwu Zhu:
NeurIPS'22 Cross-Domain MetaDL competition: Design and baseline results. CoRR abs/2208.14686 (2022) - 2021
- [j34]Clémentine Decamps, Alexis Arnaud, Florent Petitprez, Mira Ayadi, Aurélia Baurès, Lucile Armenoult, Sergio Escalera, Isabelle Guyon, Rémy Nicolle, Richard Tomasini, Aurélien de Reyniès, Jérôme Cros, Yuna Blum, Magali Richard:
DECONbench: a benchmarking platform dedicated to deconvolution methods for tumor heterogeneity quantification. BMC Bioinform. 22(1): 473 (2021) - [j33]Karan Bhanot, Miao Qi, John S. Erickson, Isabelle Guyon, Kristin P. Bennett:
The Problem of Fairness in Synthetic Healthcare Data. Entropy 23(9): 1165 (2021) - [j32]Zhengying Liu, Adrien Pavao, Zhen Xu, Sergio Escalera, Fabio Ferreira, Isabelle Guyon, Sirui Hong, Frank Hutter, Rongrong Ji, Júlio C. S. Jacques Júnior, Ge Li, Marius Lindauer, Zhipeng Luo, Meysam Madadi, Thomas Nierhoff, Kangning Niu, Chunguang Pan, Danny Stoll, Sébastien Treguer, Jin Wang, Peng Wang, Chenglin Wu, Youcheng Xiong, Arber Zela, Yang Zhang:
Winning Solutions and Post-Challenge Analyses of the ChaLearn AutoDL Challenge 2019. IEEE Trans. Pattern Anal. Mach. Intell. 43(9): 3108-3125 (2021) - [c100]Adrian El Baz, Isabelle Guyon, Zhengying Liu, Jan N. van Rijn, Sébastien Treguer, Joaquin Vanschoren:
Advances in MetaDL: AAAI 2021 Challenge and Workshop. MetaDL@AAAI 2021: 1-16 - [c99]Zhengying Liu, Isabelle Guyon:
Asymptotic Analysis of Meta-learning as a Recommendation Problem. MetaDL@AAAI 2021: 100-114 - [c98]Karan Bhanot, Saloni Dash, Joseph Pedersen, Isabelle Guyon, Kristin P. Bennett:
Quantifying Resemblance of Synthetic Medical Time-Series. ESANN 2021 - [c97]Adrien Pavao, Isabelle Guyon, Michael Vaccaro:
Judging competitions and benchmarks: a candidate election approach. ESANN 2021 - [c96]Cristina Palmero, Júlio C. S. Jacques Júnior, Albert Clapés, Isabelle Guyon, Wei-Wei Tu, Thomas B. Moeslund, Sergio Escalera:
Understanding Social Behavior in Dyadic and Small Group Interactions: Preface. DYAD@ICCV 2021: 1-3 - [c95]Cristina Palmero, Germán Barquero, Júlio C. S. Jacques Júnior, Albert Clapés, Johnny Núñez, David Curto, Sorina Smeureanu, Javier Selva, Zejian Zhang, David Saeteros, David Gallardo-Pujol, Georgina Guilera, David Leiva, Feng Han, Xiaoxue Feng, Jennifer He, Wei-Wei Tu, Thomas B. Moeslund, Isabelle Guyon, Sergio Escalera:
ChaLearn LAP Challenges on Self-Reported Personality Recognition and Non-Verbal Behavior Forecasting During Social Dyadic Interactions: Dataset, Design, and Results. DYAD@ICCV 2021: 4-52 - [c94]Germán Barquero, Johnny Núñez, Zhen Xu, Sergio Escalera, Wei-Wei Tu, Isabelle Guyon, Cristina Palmero:
Comparison of Spatio-Temporal Models for Human Motion and Pose Forecasting in Face-to-Face Interaction Scenarios. DYAD@ICCV 2021: 107-138 - [c93]Germán Barquero, Johnny Núñez, Sergio Escalera, Zhen Xu, Wei-Wei Tu, Isabelle Guyon, Cristina Palmero:
Didn't see that coming: a survey on non-verbal social human behavior forecasting. DYAD@ICCV 2021: 139-178 - [c92]Adrien Pavao, Isabelle Guyon, Nachar Stéphane, Fabrice Lebeau, Martin Ghienne, Ludovic Platon, Tristan Barbagelata, Pierre Escamilla, Sana Mzali, Meng Liao, Sylvain Lassonde, Antonin Braun, Slim Ben-Amor, Liliana Cucu-Grosjean, Marwan Wehaiba, Avner Bar-Hen, Adriana Gogonel, Alaeddine Ben Cheikh, Marc Duda, Julien Laugel, Mathieu Marauri, Mhamed Souissi, Théo Lecerf, Mehdi Elion, Sonia Tabti, Julien Budynek, Pauline Le Bouteiller, Antonin Penon, Raphaël-David Lasseri, Julien Ripoche, Thomas E. Epalle:
Aircraft Numerical "Twin": A Time Series Regression Competition. ICMLA 2021: 441-448 - [c91]Dustin Carrión-Ojeda, Mahbubul Alam, Sergio Escalera, Ahmed K. Farahat, Dipanjan Ghosh, Maria Teresa Gonzalez Diaz, Chetan Gupta, Isabelle Guyon, Joël Roman Ky, Xian Yeow Lee, Xin Liu, Felix Mohr, Manh Hung Nguyen, Emmanuel Pintelas, Stefan Roth, Simone Schaub-Meyer, Haozhe Sun, Ihsan Ullah, Joaquin Vanschoren, Lasitha Vidyaratne, Jiamin Wu, Xiaotian Yin:
NeurIPS’22 Cross-Domain MetaDL Challenge: Results and lessons learned. NeurIPS (Competition and Demos) 2021: 50-72 - [c90]Adrian El Baz, Ihsan Ullah, Edesio Alcobaça, André C. P. L. F. de Carvalho, Hong Chen, Fabio Ferreira, Henry Gouk, Chaoyu Guan, Isabelle Guyon, Timothy M. Hospedales, Shell Hu, Mike Huisman, Frank Hutter, Zhengying Liu, Felix Mohr, Ekrem Öztürk, Jan N. van Rijn, Haozhe Sun, Xin Wang, Wenwu Zhu:
Lessons learned from the NeurIPS 2021 MetaDL challenge: Backbone fine-tuning without episodic meta-learning dominates for few-shot learning image classification. NeurIPS (Competition and Demos) 2021: 80-96 - [c89]Haozhe Sun, Wei-Wei Tu, Isabelle Guyon:
OmniPrint: A Configurable Printed Character Synthesizer. NeurIPS Datasets and Benchmarks 2021 - [c88]Sebastian Weichwald, Søren Wengel Mogensen, Tabitha Edith Lee, Dominik Baumann, Oliver Kroemer, Isabelle Guyon, Sebastian Trimpe, Jonas Peters, Niklas Pfister:
Learning by Doing: Controlling a Dynamical System using Causality, Control, and Reinforcement Learning. NeurIPS (Competition and Demos) 2021: 246-258 - [c87]Manh Hung Nguyen, Isabelle Guyon, Lisheng Sun-Hosoya, Nathan Grinsztajn:
MetaREVEAL: RL-based Meta-learning from Learning Curves. IAL@PKDD/ECML 2021: 1-20 - [c86]Zhen Xu, Wei-Wei Tu, Isabelle Guyon:
AutoML Meets Time Series Regression Design and Analysis of the AutoSeries Challenge. ECML/PKDD (5) 2021: 36-51 - [c85]Romain Égelé, Prasanna Balaprakash, Isabelle Guyon, Venkatram Vishwanath, Fangfang Xia, Rick Stevens, Zhengying Liu:
AgEBO-tabular: joint neural architecture and hyperparameter search with autotuned data-parallel training for tabular data. SC 2021: 30 - [e13]Isabelle Guyon, Jan N. van Rijn, Sébastien Treguer, Joaquin Vanschoren:
AAAI Workshop on Meta-Learning and MetaDL Challenge, MetaDL@AAAI 2021, virtual, February 9, 2021. Proceedings of Machine Learning Research 140, PMLR 2021 [contents] - [e12]Cristina Palmero, Júlio C. S. Jacques Júnior, Albert Clapés, Isabelle Guyon, Wei-Wei Tu, Thomas B. Moeslund, Sergio Escalera:
ChaLearn LAP Challenge on Understanding Social Behavior in Dyadic and Small Group Interactions, DYAD 2021, held in conjunction with ICCV 2021, Virtual, October 16, 2021. Proceedings of Machine Learning Research 173, PMLR 2021 [contents] - [i23]Antoine Marot, Benjamin Donnot, Gabriel Dulac-Arnold, Adrian Kelly, Aïdan O'Sullivan, Jan Viebahn, Mariette Awad, Isabelle Guyon, Patrick Panciatici, Camilo Romero:
Learning to run a Power Network Challenge: a Retrospective Analysis. CoRR abs/2103.03104 (2021) - [i22]Ryan Turner, David Eriksson, Michael McCourt, Juha Kiili, Eero Laaksonen, Zhen Xu, Isabelle Guyon:
Bayesian Optimization is Superior to Random Search for Machine Learning Hyperparameter Tuning: Analysis of the Black-Box Optimization Challenge 2020. CoRR abs/2104.10201 (2021) - [i21]Sabrina Amrouche, Laurent Basara, Paolo Calafiura, Dmitry Emeliyanov, Victor Estrade, Steven Farrell, Cécile Germain, Vladimir Vava Gligorov, Tobias Golling, Sergey Gorbunov, Heather M. Gray, Isabelle Guyon, Mikhail Hushchyn, Vincenzo Innocente, Moritz Kiehn, Marcel Kunze, Edward Moyse, David Rousseau, Andreas Salzburger, Andrey Ustyuzhanin, Jean-Roch Vlimant:
The Tracking Machine Learning challenge : Throughput phase. CoRR abs/2105.01160 (2021) - [i20]Sergio Escalera, Marti Soler, Stéphane Ayache, Umut Güçlü, Jun Wan, Meysam Madadi, Xavier Baró, Hugo Jair Escalante, Isabelle Guyon:
ChaLearn Looking at People: Inpainting and Denoising challenges. CoRR abs/2106.13071 (2021) - [i19]Zhen Xu, Wei-Wei Tu, Isabelle Guyon:
AutoML Meets Time Series Regression Design and Analysis of the AutoSeries Challenge. CoRR abs/2107.13186 (2021) - [i18]Zhen Xu, Huan Zhao, Wei-Wei Tu, Magali Richard, Sergio Escalera, Isabelle Guyon:
Codabench: Flexible, Easy-to-Use and Reproducible Benchmarking for Everyone. CoRR abs/2110.05802 (2021) - 2020
- [j31]Andrew Yale, Saloni Dash, Ritik Dutta, Isabelle Guyon, Adrien Pavao, Kristin P. Bennett:
Generation and evaluation of privacy preserving synthetic health data. Neurocomputing 416: 244-255 (2020) - [j30]Balthazar Donon, Benjamin Donnot, Isabelle Guyon, Zhengying Liu, Antoine Marot, Patrick Panciatici, Marc Schoenauer:
LEAP nets for system identification and application to power systems. Neurocomputing 416: 316-327 (2020) - [j29]Sergio Escalera, Hugo Jair Escalante, Xavier Baró, Isabelle Guyon, Meysam Madadi, Jun Wan, Stéphane Ayache, Yagmur Güçlütürk, Umut Güçlü:
Guest Editorial: Image and Video Inpainting and Denoising. IEEE Trans. Pattern Anal. Mach. Intell. 42(5): 1021-1024 (2020) - [j28]Zhengying Liu, Zhen Xu, Sergio Escalera, Isabelle Guyon, Júlio C. S. Jacques Júnior, Meysam Madadi, Adrien Pavao, Sébastien Treguer, Wei-Wei Tu:
Towards automated computer vision: analysis of the AutoCV challenges 2019. Pattern Recognit. Lett. 135: 196-203 (2020) - [c84]Saloni Dash, Andrew Yale, Isabelle Guyon, Kristin P. Bennett:
Medical Time-Series Data Generation Using Generative Adversarial Networks. AIME 2020: 382-391 - [c83]Andrew Yale, Saloni Dash, Karan Bhanot, Isabelle Guyon, John S. Erickson, Kristin P. Bennett:
Synthesizing Quality Open Data Assets from Private Health Research Studies. BIS (Workshops) 2020: 324-335 - [c82]Rishabh Mehrotra, Ben Carterette, Yong Li, Quanming Yao, Chen Gao, James T. Kwok, Qiang Yang, Isabelle Guyon:
Advances in Recommender Systems: From Multi-stakeholder Marketplaces to Automated RecSys. KDD 2020: 3533-3534 - [c81]Balthazar Donon, Zhengying Liu, Wenzhuo Liu, Isabelle Guyon, Antoine Marot, Marc Schoenauer:
Deep Statistical Solvers. NeurIPS 2020 - [c80]Ryan Turner, David Eriksson, Michael McCourt, Juha Kiili, Eero Laaksonen, Zhen Xu, Isabelle Guyon:
Bayesian Optimization is Superior to Random Search for Machine Learning Hyperparameter Tuning: Analysis of the Black-Box Optimization Challenge 2020. NeurIPS (Competition and Demos) 2020: 3-26 - [c79]Meysam Madadi, Hugo Bertiche, Wafa Bouzouita, Isabelle Guyon, Sergio Escalera:
Learning Cloth Dynamics: 3D+Texture Garment Reconstruction Benchmark. NeurIPS (Competition and Demos) 2020: 57-76 - [c78]Antoine Marot, Benjamin Donnot, Gabriel Dulac-Arnold, Adrian Kelly, Aidan O'Sullivan, Jan Viebahn, Mariette Awad, Isabelle Guyon, Patrick Panciatici, Camilo Romero:
Learning to run a Power Network Challenge: a Retrospective Analysis. NeurIPS (Competition and Demos) 2020: 112-132 - [c77]Yiding Jiang, Parth Natekar, Manik Sharma, Sumukh K. Aithal, Dhruva Kashyap, Natarajan Subramanyam, Carlos Lassance, Daniel M. Roy, Gintare Karolina Dziugaite, Suriya Gunasekar, Isabelle Guyon, Pierre Foret, Scott Yak, Hossein Mobahi, Behnam Neyshabur, Samy Bengio:
Methods and Analysis of The First Competition in Predicting Generalization of Deep Learning. NeurIPS (Competition and Demos) 2020: 170-190 - [i17]Romain Egele, Prasanna Balaprakash, Venkatram Vishwanath, Isabelle Guyon, Zhengying Liu:
AgEBO-Tabular: Joint Neural Architecture and Hyperparameter Search with Autotuned Data-Parallel Training for Tabular Data. CoRR abs/2010.16358 (2020) - [i16]Yiding Jiang, Pierre Foret, Scott Yak, Daniel M. Roy, Hossein Mobahi, Gintare Karolina Dziugaite, Samy Bengio, Suriya Gunasekar, Isabelle Guyon, Behnam Neyshabur:
NeurIPS 2020 Competition: Predicting Generalization in Deep Learning. CoRR abs/2012.07976 (2020)
2010 – 2019
- 2019
- [j27]Borja Seijo-Pardo, Amparo Alonso-Betanzos, Kristin P. Bennett, Verónica Bolón-Canedo, Julie Josse, Mehreen Saeed, Isabelle Guyon:
Biases in feature selection with missing data. Neurocomputing 342: 97-112 (2019) - [c76]Andrew Yale, Saloni Dash, Ritik Dutta, Isabelle Guyon, Adrien Pavao, Kristin P. Bennett:
Assessing privacy and quality of synthetic health data. AIDR 2019: 8:1-8:4 - [c75]Ajian Liu, Jun Wan, Sergio Escalera, Hugo Jair Escalante, Zichang Tan, Qi Yuan, Kai Wang, Chi Lin, Guodong Guo, Isabelle Guyon, Stan Z. Li:
Multi-Modal Face Anti-Spoofing Attack Detection Challenge at CVPR2019. CVPR Workshops 2019: 1601-1610 - [c74]Benjamin Donnot, Balthazar Donon, Isabelle Guyon, Zhengying Liu, Antoine Marot, Patrick Panciatici, Marc Schoenauer:
LEAP nets for power grid perturbations. ESANN 2019 - [c73]Andrew Yale, Saloni Dash, Ritik Dutta, Isabelle Guyon, Adrien Pavao, Kristin P. Bennett:
Privacy Preserving Synthetic Health Data. ESANN 2019 - [c72]Balthazar Donon, Benjamin Donnot, Isabelle Guyon, Antoine Marot:
Graph Neural Solver for Power Systems. IJCNN 2019: 1-8 - [c71]Zhengying Liu, Zhen Xu, Shangeth Rajaa, Meysam Madadi, Júlio C. S. Jacques Júnior, Sergio Escalera, Adrien Pavao, Sébastien Treguer, Wei-Wei Tu, Isabelle Guyon:
Towards Automated Deep Learning: Analysis of the AutoDL challenge series 2019. NeurIPS (Competition and Demos) 2019: 242-252 - [p11]Isabelle Guyon, Olivier Goudet, Diviyan Kalainathan:
Evaluation Methods of Cause-Effect Pairs. Cause Effect Pairs in Machine Learning 2019: 27-99 - [p10]Olivier Goudet, Diviyan Kalainathan, Michèle Sebag, Isabelle Guyon:
Learning Bivariate Functional Causal Models. Cause Effect Pairs in Machine Learning 2019: 101-153 - [p9]Diviyan Kalainathan, Olivier Goudet, Michèle Sebag, Isabelle Guyon:
Discriminant Learning Machines. Cause Effect Pairs in Machine Learning 2019: 155-189 - [p8]Isabelle Guyon, Lisheng Sun-Hosoya, Marc Boullé, Hugo Jair Escalante, Sergio Escalera, Zhengying Liu, Damir Jajetic, Bisakha Ray, Mehreen Saeed, Michèle Sebag, Alexander R. Statnikov, Wei-Wei Tu, Evelyne Viegas:
Analysis of the AutoML Challenge Series 2015-2018. Automated Machine Learning 2019: 177-219 - [p7]Isabelle Guyon, Alexander R. Statnikov:
Results of the Cause-Effect Pair Challenge. Cause Effect Pairs in Machine Learning 2019: 237-256 - [e11]Isabelle Guyon, Alexander R. Statnikov, Berna Bakir Batu:
Cause Effect Pairs in Machine Learning. Springer 2019, ISBN 978-3-030-21809-6 [contents] - [i15]Hugo Jair Escalante, Wei-Wei Tu, Isabelle Guyon, Daniel L. Silver, Evelyne Viegas, Yuqiang Chen, Wenyuan Dai, Qiang Yang:
AutoML @ NeurIPS 2018 challenge: Design and Results. CoRR abs/1903.05263 (2019) - [i14]Jorge G. Madrid, Hugo Jair Escalante, Eduardo F. Morales, Wei-Wei Tu, Yang Yu, Lisheng Sun-Hosoya, Isabelle Guyon, Michèle Sebag:
Towards AutoML in the presence of Drift: first results. CoRR abs/1907.10772 (2019) - [i13]Jun Wan, Chi Lin, Longyin Wen, Yunan Li, Qiguang Miao, Sergio Escalera, Gholamreza Anbarjafari, Isabelle Guyon, Guodong Guo, Stan Z. Li:
ChaLearn Looking at People: IsoGD and ConGD Large-scale RGB-D Gesture Recognition. CoRR abs/1907.12193 (2019) - [i12]Benjamin Donnot, Balthazar Donon, Isabelle Guyon, Zhengying Liu, Antoine Marot, Patrick Panciatici, Marc Schoenauer:
LEAP nets for power grid perturbations. CoRR abs/1908.08314 (2019) - [i11]Saloni Dash, Ritik Dutta, Isabelle Guyon, Adrien Pavao, Andrew Yale, Kristin P. Bennett:
Synthetic Event Time Series Health Data Generation. CoRR abs/1911.06411 (2019) - [i10]Antoine Marot, Benjamin Donnot, Camilo Romero, Luca Veyrin-Forrer, Marvin Lerousseau, Balthazar Donon, Isabelle Guyon:
Learning to run a power network challenge for training topology controllers. CoRR abs/1912.04211 (2019) - 2018
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