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20192022
most citedHyper-Parameter Auto-Tuning for Sparse Bayesian Learning

1 citations · 1 across the 3 of their papers we have counts for

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eess.SP20221 cited

Hyper-Parameter Auto-Tuning for Sparse Bayesian Learning

Dawei Gao, Qinghua Guo, Ming Jin +2

Choosing the values of hyper-parameters in sparse Bayesian learning (SBL) can significantly impact performance. However, the hyper-parameters are normally tuned manually, which is…

eess.SP2022

Signal Detection in MIMO Systems with Hardware Imperfections: Message Passing on Neural Networks

Dawei Gao, Qinghua Guo, Guisheng Liao +4

In this paper, we investigate signal detection in multiple-input-multiple-output (MIMO) communication systems with hardware impairments, such as power amplifier nonlinearity and in…

eess.SP2020

Massive MIMO As an Extreme Learning Machine

Dawei Gao, Qinghua Guo, Yonina C. Eldar

This work shows that a massive multiple-input multiple-output (MIMO) system with low-resolution analog-to-digital converters (ADCs) forms a natural extreme learning machine (ELM).…

eess.SP2019

Extreme Learning Machine Based Non-Iterative and Iterative Nonlinearity Mitigation for LED Communications

Dawei Gao, Qinghua Guo, Jun Tong +3

This work concerns receiver design for light emitting diode (LED) communications where the LED nonlinearity can severely degrade the performance of communications. We propose extre…

eess.SP2019

Extreme Learning Machine-Based Receiver for MIMO LED Communications

Dawei Gao, Qinghua Guo

This work concerns receiver design for light-emitting diode (LED) multiple input multiple output (MIMO) communications where the LED nonlinearity can severely degrade the performan…