Differentiable Neural Architecture Search for High-Dimensional Time Series Forecasting

Differentiable Neural Architecture Search for High-Dimensional Time Series Forecasting

This study applies neural architecture search (NAS) techniques to the modeling of high-dimensional time series data such as multi-variate stock indices. It is known that traditional NAS method applies fully connected directed acyclic graph (DAG) for searching cell structures that requires high compu...

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Bibliographic Details
Main Authors: Renlong Jie, Junbin Gao
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
DA-RNN
DARTS backbone
neural architecture search
stacked RNN
time series forecasting
Online Access:https://ieeexplore.ieee.org/document/9340253/

Internet

https://ieeexplore.ieee.org/document/9340253/

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