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2020 – today
- 2024
[i9]Abdul Fatir Ansari, Lorenzo Stella, Ali Caner Türkmen, Xiyuan Zhang, Pedro Mercado, Huibin Shen, Oleksandr Shchur, Syama Sundar Rangapuram, Sebastian Pineda-Arango, Shubham Kapoor, Jasper Zschiegner, Danielle C. Maddix, Michael W. Mahoney, Kari Torkkola, Andrew Gordon Wilson, Michael Bohlke-Schneider, Yuyang Wang:
Chronos: Learning the Language of Time Series. CoRR abs/2403.07815 (2024)- 2023
- [c7]Oleksandr Shchur, Ali Caner Türkmen, Nick Erickson, Huibin Shen, Alexander Shirkov, Tony Hu, Bernie Wang:
AutoGluon-TimeSeries: AutoML for Probabilistic Time Series Forecasting. AutoML 2023: 9/1-21 - [i8]Mike Van Ness, Huibin Shen, Hao Wang, Xiaoyong Jin, Danielle C. Maddix, Karthick Gopalswamy:
Cross-Frequency Time Series Meta-Forecasting. CoRR abs/2302.02077 (2023) - [i7]Sigrid Passano Hellan, Huibin Shen, François-Xavier Aubet, David Salinas, Aaron Klein:
Obeying the Order: Introducing Ordered Transfer Hyperparameter Optimisation. CoRR abs/2306.16916 (2023) - [i6]Oleksandr Shchur, Ali Caner Türkmen, Nick Erickson, Huibin Shen, Alexander Shirkov, Tony Hu, Yuyang Wang:
AutoGluon-TimeSeries: AutoML for Probabilistic Time Series Forecasting. CoRR abs/2308.05566 (2023) - 2022
- [c6]Anastasia Makarova, Huibin Shen, Valerio Perrone, Aaron Klein, Jean Baptiste Faddoul, Andreas Krause, Matthias W. Seeger, Cédric Archambeau:
Automatic Termination for Hyperparameter Optimization. AutoML 2022: 7/1-21 - 2021
- [c5]Valerio Perrone, Huibin Shen, Aida Zolic, Iaroslav Shcherbatyi, Amr Ahmed, Tanya Bansal, Michele Donini, Fela Winkelmolen, Rodolphe Jenatton, Jean Baptiste Faddoul, Barbara Pogorzelska, Miroslav Miladinovic, Krishnaram Kenthapadi, Matthias W. Seeger, Cédric Archambeau:
Amazon SageMaker Automatic Model Tuning: Scalable Gradient-Free Optimization. KDD 2021: 3463-3471 - [i5]Anastasia Makarova, Huibin Shen, Valerio Perrone, Aaron Klein, Jean Baptiste Faddoul, Andreas Krause, Matthias W. Seeger, Cédric Archambeau:
Overfitting in Bayesian Optimization: an empirical study and early-stopping solution. CoRR abs/2104.08166 (2021) - 2020
- [c4]David Salinas, Huibin Shen, Valerio Perrone:
A Quantile-based Approach for Hyperparameter Transfer Learning. ICML 2020: 8438-8448 - [c3]Piali Das, Nikita Ivkin, Tanya Bansal, Laurence Rouesnel, Philip Gautier, Zohar S. Karnin, Leo Dirac, Lakshmi Ramakrishnan, Andre Perunicic, Iaroslav Shcherbatyi, Wilton Wu, Aida Zolic, Huibin Shen, Amr Ahmed, Fela Winkelmolen, Miroslav Miladinovic, Cédric Archambeau, Alex Tang, Bhaskar Dutt, Patricia Grao, Kumar Venkateswar:
Amazon SageMaker Autopilot: a white box AutoML solution at scale. DEEM@SIGMOD 2020: 2:1-2:7 - [i4]Piali Das, Valerio Perrone, Nikita Ivkin, Tanya Bansal, Zohar S. Karnin, Huibin Shen, Iaroslav Shcherbatyi, Yotam Elor, Wilton Wu, Aida Zolic, Thibaut Liénart, Alex Tang, Amr Ahmed, Jean Baptiste Faddoul, Rodolphe Jenatton, Fela Winkelmolen, Philip Gautier, Leo Dirac, Andre Perunicic, Miroslav Miladinovic, Giovanni Zappella, Cédric Archambeau, Matthias W. Seeger, Bhaskar Dutt, Laurence Rouesnel:
Amazon SageMaker Autopilot: a white box AutoML solution at scale. CoRR abs/2012.08483 (2020) - [i3]Valerio Perrone, Huibin Shen, Aida Zolic, Iaroslav Shcherbatyi, Amr Ahmed, Tanya Bansal, Michele Donini, Fela Winkelmolen, Rodolphe Jenatton, Jean Baptiste Faddoul, Barbara Pogorzelska, Miroslav Miladinovic, Krishnaram Kenthapadi, Matthias W. Seeger, Cédric Archambeau:
Amazon SageMaker Automatic Model Tuning: Scalable Black-box Optimization. CoRR abs/2012.08489 (2020)
2010 – 2019
- 2019
- [c2]Valerio Perrone, Huibin Shen:
Learning search spaces for Bayesian optimization: Another view of hyperparameter transfer learning. NeurIPS 2019: 12751-12761 - [i2]Valerio Perrone, Huibin Shen, Matthias W. Seeger, Cédric Archambeau, Rodolphe Jenatton:
Learning search spaces for Bayesian optimization: Another view of hyperparameter transfer learning. CoRR abs/1909.12552 (2019) - [i1]David Salinas, Huibin Shen, Valerio Perrone:
A Copula approach for hyperparameter transfer learning. CoRR abs/1909.13595 (2019) - 2017
- [b1]Huibin Shen:
Machine Learning for Small Molecule Identification. Aalto University, Helsinki, Finland, 2017 - [j4]Emma Schymanski
, Christoph Ruttkies, Martin Krauss, Céline Brouard, Tobias Kind, Kai Dührkop, Felicity Allen, Arpana Vaniya, Dries Verdegem, Sebastian Böcker, Juho Rousu, Huibin Shen, Hiroshi Tsugawa, Tanvir Sajed, Oliver Fiehn, Bart Ghesquière, Steffen Neumann:
Critical Assessment of Small Molecule Identification 2016: automated methods. J. Cheminformatics 9(1): 22:1-22:21 (2017) - 2016
- [j3]Céline Brouard, Huibin Shen, Kai Dührkop, Florence d'Alché-Buc, Sebastian Böcker, Juho Rousu:
Fast metabolite identification with Input Output Kernel Regression. Bioinform. 32(12): 28-36 (2016) - [c1]Huibin Shen, Sándor Szedmák, Céline Brouard, Juho Rousu:
Soft Kernel Target Alignment for Two-Stage Multiple Kernel Learning. DS 2016: 427-441 - 2014
- [j2]Huibin Shen, Kai Dührkop, Sebastian Böcker, Juho Rousu:
Metabolite identification through multiple kernel learning on fragmentation trees. Bioinform. 30(12): 157-164 (2014) - 2012
- [j1]Markus Heinonen, Huibin Shen, Nicola Zamboni, Juho Rousu:
Metabolite identification and molecular fingerprint prediction through machine learning. Bioinform. 28(18): 2333-2341 (2012)
Coauthor Index
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