Huibin Shen

Publication Activity (10 Years)

Years Active: 2012-2024
Publications (10 Years): 18

Top Venues

CoRR

Bioinform.

AutoML

KDD

Aalto University, Helsinki, Finland (PHD)

Education History

Aalto University, Helsinki, Finland

PHD

Publications

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 (2024)
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)
Mike Van Ness, Huibin Shen, Hao Wang, Xiaoyong Jin, Danielle C. Maddix, Karthick Gopalswamy
Cross-Frequency Time Series Meta-Forecasting. CoRR (2023)
Oleksandr Shchur, Ali Caner Türkmen, Nick Erickson, Huibin Shen, Alexander Shirkov, Tony Hu, Yuyang Wang
AutoGluon-TimeSeries: AutoML for Probabilistic Time Series Forecasting. CoRR (2023)
Sigrid Passano Hellan, Huibin Shen, François-Xavier Aubet, David Salinas, Aaron Klein
Obeying the Order: Introducing Ordered Transfer Hyperparameter Optimisation. CoRR (2023)
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)
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)
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 (2021)
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 (2020)
David Salinas, Huibin Shen, Valerio Perrone
A Quantile-based Approach for Hyperparameter Transfer Learning. ICML (2020)
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)
Piali Das, Valerio Perrone, Nikita Ivkin, Tanya Bansal, Zohar S. Karnin, Huibin Shen, Iaroslav Shcherbatyi, Yotam Elor, Wilton Wu, Aida Zolic, Thibaut Lienart, 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 (2020)
Valerio Perrone, Huibin Shen, Matthias W. Seeger, Cédric Archambeau, Rodolphe Jenatton
Learning search spaces for Bayesian optimization: Another view of hyperparameter transfer learning. CoRR (2019)
Valerio Perrone, Huibin Shen
Learning search spaces for Bayesian optimization: Another view of hyperparameter transfer learning. NeurIPS (2019)
David Salinas, Huibin Shen, Valerio Perrone
A Copula approach for hyperparameter transfer learning. CoRR (2019)
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) (2017)
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) (2016)
Huibin Shen, Sándor Szedmák, Céline Brouard, Juho Rousu
Soft Kernel Target Alignment for Two-Stage Multiple Kernel Learning. DS (2016)
Huibin Shen, Kai Dührkop, Sebastian Böcker, Juho Rousu
Metabolite identification through multiple kernel learning on fragmentation trees. Bioinform. 30 (12) (2014)
Markus Heinonen, Huibin Shen, Nicola Zamboni, Juho Rousu
Metabolite identification and molecular fingerprint prediction through machine learning. Bioinform. 28 (18) (2012)

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Publication Activity (10 Years)

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Huibin Shen