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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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