An Efficient and Effective Second-Order Training Algorithm for LSTM-Based Adaptive Learning

We study adaptive (or online) nonlinear regression with Long-Short-Term-Memory (LSTM) based networks, i.e., LSTM-based adaptive learning. In this context, we introduce an efficient Extended Kalman filter (EKF) based second-order training algorithm. Our algorithm is truly online, i.e., it does not as...

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Vydáno v:	IEEE transactions on signal processing Ročník 69; s. 2541 - 2554
Hlavní autoři:	Vural, N. Mert, Ergut, Salih, Kozat, Suleyman S.
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York IEEE 2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	Adaptation models Adaptive algorithms Adaptive learning Adaptive systems Algorithms Approximation algorithms Extended Kalman filter Kalman filtering long short term memory (LSTM) Machine learning MLR-DEEP online learning Prediction algorithms regression Signal processing algorithms stochastic gradient descent (SGD) EDICS Category: MLR-SLER Training truly online
ISSN:	1053-587X, 1941-0476
On-line přístup:	Získat plný text
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