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Kaggle forecasting competitions: An overlooked learning opportunity

Kaggle forecasting competitions: An overlooked learning opportunity

Casper Solheim Bojer
Jens Peder Meldgaard
ArXiv (abs)PDFHTML

Papers citing "Kaggle forecasting competitions: An overlooked learning opportunity"

6 / 6 papers shown
Title
Criteria for Classifying Forecasting Methods
Criteria for Classifying Forecasting Methods
Tim Januschowski
Jan Gasthaus
Bernie Wang
David Salinas
Valentin Flunkert
Michael Bohlke-Schneider
Laurent Callot
AI4TS
68
178
0
07 Dec 2022
NGBoost: Natural Gradient Boosting for Probabilistic Prediction
NGBoost: Natural Gradient Boosting for Probabilistic Prediction
Tony Duan
Anand Avati
D. Ding
Khanh K. Thai
S. Basu
A. Ng
Alejandro Schuler
BDL
34
303
0
08 Oct 2019
Averaging Weights Leads to Wider Optima and Better Generalization
Averaging Weights Leads to Wider Optima and Better Generalization
Pavel Izmailov
Dmitrii Podoprikhin
T. Garipov
Dmitry Vetrov
A. Wilson
FedMLMoMe
135
1,669
0
14 Mar 2018
DeepAR: Probabilistic Forecasting with Autoregressive Recurrent Networks
DeepAR: Probabilistic Forecasting with Autoregressive Recurrent Networks
David Salinas
Valentin Flunkert
Jan Gasthaus
AI4TSUQCVBDL
81
2,112
0
13 Apr 2017
Entity Embeddings of Categorical Variables
Entity Embeddings of Categorical Variables
Cheng Guo
Felix Berkhahn
79
64
0
22 Apr 2016
XGBoost: A Scalable Tree Boosting System
XGBoost: A Scalable Tree Boosting System
Tianqi Chen
Carlos Guestrin
809
38,961
0
09 Mar 2016

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