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Multi-objective Asynchronous Successive Halving


Jun 23, 2021
Robin Schmucker, Michele Donini, Muhammad Bilal Zafar, David Salinas, Cédric Archambeau


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A multi-objective perspective on jointly tuning hardware and hyperparameters


Jun 10, 2021
David Salinas, Valerio Perrone, Olivier Cruchant, Cedric Archambeau


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A resource-efficient method for repeated HPO and NAS problems


Mar 30, 2021
Giovanni Zappella, David Salinas, Cédric Archambeau


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The Effectiveness of Discretization in Forecasting: An Empirical Study on Neural Time Series Models


May 20, 2020
Stephan Rabanser, Tim Januschowski, Valentin Flunkert, David Salinas, Jan Gasthaus


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Neural forecasting: Introduction and literature overview


Apr 21, 2020
Konstantinos Benidis, Syama Sundar Rangapuram, Valentin Flunkert, Bernie Wang, Danielle Maddix, Caner Turkmen, Jan Gasthaus, Michael Bohlke-Schneider, David Salinas, Lorenzo Stella, Laurent Callot, Tim Januschowski

* 66 pages, 5 figures 

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High-Dimensional Multivariate Forecasting with Low-Rank Gaussian Copula Processes


Oct 24, 2019
David Salinas, Michael Bohlke-Schneider, Laurent Callot, Roberto Medico, Jan Gasthaus


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A Copula approach for hyperparameter transfer learning


Sep 30, 2019
David Salinas, Huibin Shen, Valerio Perrone


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GluonTS: Probabilistic Time Series Models in Python


Jun 14, 2019
Alexander Alexandrov, Konstantinos Benidis, Michael Bohlke-Schneider, Valentin Flunkert, Jan Gasthaus, Tim Januschowski, Danielle C. Maddix, Syama Rangapuram, David Salinas, Jasper Schulz, Lorenzo Stella, Ali Caner Türkmen, Yuyang Wang

* ICML Time Series Workshop 2019 

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Approximate Bayesian Inference in Linear State Space Models for Intermittent Demand Forecasting at Scale


Sep 22, 2017
Matthias Seeger, Syama Rangapuram, Yuyang Wang, David Salinas, Jan Gasthaus, Tim Januschowski, Valentin Flunkert


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DeepAR: Probabilistic Forecasting with Autoregressive Recurrent Networks


Jul 05, 2017
Valentin Flunkert, David Salinas, Jan Gasthaus


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