Generalized Exponentiated Gradient Algorithms and Their Application to On-Line Portfolio Selection
Stochastic gradient descent (SGD) and exponentiated gradient (EG) update methods are widely used in signal processing and machine learning. This study introduces a novel family of generalized Exponentiated Gradient updates (EGAB) derived from the alpha-beta (AB) divergence regularization. The EGAB f...
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| Main Authors: | Andrzej Cichocki, Sergio Cruces, Auxiliadora Sarmiento, Toshihisa Tanaka |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2024-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10807168/ |
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