Huibin Shen - RankMe

26 papers A* 3A 1B 1Journal 16Unranked 4

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Chronos-2: From Univariate to Universal Forecasting. CoRR Abdul Fatir Ansari, Oleksandr Shchur, Jaris Küken, Andreas Auer, Boran Han, Pedro Mercado, Syama Sundar Rangapuram, Huibin Shen, Lorenzo Stella, Xiyuan Zhang, Mononito Goswami, Shubham Kapoor, Danielle C. Maddix, Pablo Guerron, Tony Hu, Junming Yin, Nick Erickson, Prateek Mutalik Desai, Hao Wang, Huzefa Rangwala, George Karypis, Yuyang Wang, Michael Bohlke-Schneider
2025	A	`conf`	ChronosX: Adapting Pretrained Time Series Models with Exogenous Variables. AISTATS Sebastian Pineda Arango, Pedro Mercado, Shubham Kapoor, Abdul Fatir Ansari, Lorenzo Stella, Huibin Shen, Hugo Senetaire, Ali Caner Türkmen, Oleksandr Shchur, Danielle C. Maddix, Michael Bohlke-Schneider, Bernie Wang, Syama Sundar Rangapuram
2025	J	`jnl`	ChronosX: Adapting Pretrained Time Series Models with Exogenous Variables. CoRR Sebastian Pineda-Arango, Pedro Mercado, Shubham Kapoor, Abdul Fatir Ansari, Lorenzo Stella, Huibin Shen, Hugo Senetaire, Caner Turkmen, Oleksandr Shchur, Danielle C. Maddix, Michael Bohlke-Schneider, Yuyang Wang, Syama Sundar Rangapuram
2025	—	`conf`	Obeying the Order: Introducing Ordered Transfer Hyperparameter Optimization. AutoML Sigrid Passano Hellan, Huibin Shen, Francois-Xavier Aubet, David Salinas, Aaron Klein
2024	J	`jnl`	Chronos: Learning the Language of Time Series. CoRR 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
2024	J	`jnl`	Chronos: Learning the Language of Time Series. Trans. Mach. Learn. Res. 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, Hao Wang, Michael W. Mahoney, Kari Torkkola, Andrew Gordon Wilson, Michael Bohlke-Schneider, Bernie Wang
2023	—	`conf`	AutoGluon-TimeSeries: AutoML for Probabilistic Time Series Forecasting. AutoML Oleksandr Shchur, Ali Caner Türkmen, Nick Erickson, Huibin Shen, Alexander Shirkov, Tony Hu, Bernie Wang
2023	J	`jnl`	AutoGluon-TimeSeries: AutoML for Probabilistic Time Series Forecasting. CoRR Oleksandr Shchur, Ali Caner Türkmen, Nick Erickson, Huibin Shen, Alexander Shirkov, Tony Hu, Yuyang Wang
2023	J	`jnl`	Cross-Frequency Time Series Meta-Forecasting. CoRR Mike Van Ness, Huibin Shen, Hao Wang, Xiaoyong Jin, Danielle C. Maddix, Karthick Gopalswamy
2023	J	`jnl`	Obeying the Order: Introducing Ordered Transfer Hyperparameter Optimisation. CoRR Sigrid Passano Hellan, Huibin Shen, François-Xavier Aubet, David Salinas, Aaron Klein
2022	—	`conf`	Automatic Termination for Hyperparameter Optimization. AutoML Anastasia Makarova, Huibin Shen, Valerio Perrone, Aaron Klein, Jean Baptiste Faddoul, Andreas Krause, Matthias W. Seeger, Cédric Archambeau
2021	A*	`conf`	Amazon SageMaker Automatic Model Tuning: Scalable Gradient-Free Optimization. KDD 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
2021	J	`jnl`	Overfitting in Bayesian Optimization: an empirical study and early-stopping solution. CoRR Anastasia Makarova, Huibin Shen, Valerio Perrone, Aaron Klein, Jean Baptiste Faddoul, Andreas Krause, Matthias W. Seeger, Cédric Archambeau
2020	A*	`conf`	A Quantile-based Approach for Hyperparameter Transfer Learning. ICML David Salinas, Huibin Shen, Valerio Perrone
2020	J	`jnl`	Amazon SageMaker Automatic Model Tuning: Scalable Black-box Optimization. CoRR 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
2020	—	`conf`	Amazon SageMaker Autopilot: a white box AutoML solution at scale. DEEM@SIGMOD 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
2020	J	`jnl`	Amazon SageMaker Autopilot: a white box AutoML solution at scale. CoRR 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
2019	J	`jnl`	A Copula approach for hyperparameter transfer learning. CoRR David Salinas, Huibin Shen, Valerio Perrone
2019	A*	`conf`	Learning search spaces for Bayesian optimization: Another view of hyperparameter transfer learning. NeurIPS Valerio Perrone, Huibin Shen
2019	J	`jnl`	Learning search spaces for Bayesian optimization: Another view of hyperparameter transfer learning. CoRR Valerio Perrone, Huibin Shen, Matthias W. Seeger, Cédric Archambeau, Rodolphe Jenatton
2017	J	`jnl`	Critical Assessment of Small Molecule Identification 2016: automated methods. J. Cheminformatics 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
2017	—	`—`	Machine Learning for Small Molecule Identification. Huibin Shen
2016	J	`jnl`	Fast metabolite identification with Input Output Kernel Regression. Bioinform. Céline Brouard, Huibin Shen, Kai Dührkop, Florence d'Alché-Buc, Sebastian Böcker, Juho Rousu
2016	B	`conf`	Soft Kernel Target Alignment for Two-Stage Multiple Kernel Learning. DS Huibin Shen, Sándor Szedmák, Céline Brouard, Juho Rousu
2014	J	`jnl`	Metabolite identification through multiple kernel learning on fragmentation trees. Bioinform. Huibin Shen, Kai Dührkop, Sebastian Böcker, Juho Rousu
2012	J	`jnl`	Metabolite identification and molecular fingerprint prediction through machine learning. Bioinform. Markus Heinonen, Huibin Shen, Nicola Zamboni, Juho Rousu