Hongxuan Wang — accepted AI-conference papers

2025

Safe Bayesian Optimization for Complex Control Systems via Additive Gaussian Processes

Hongxuan Wang, Xiaocong Li, Lihao Zheng, Adrish Bhaumik, Prahlad Vadakkepat

RA-L 2025

Controller tuning and optimization have long been recognized as fundamental challenges in robotics and mechatronic systems. Traditional controller design techniques are usually model-based, and their closed-loop performance depends on the fidelity of the mathematical model. Subsequent tuning of the

Cited by 1 Source ↗Scholar ↗

2024

Gradient-Based Dimensionality Reduction for Speech Emotion Recognition Using Deep Networks

Hongxuan Wang, Prahlad Vadakkepat

ICASSP 2024accepted

This paper introduces a gradient-based approach for reducing the dimensionality of acoustic features, tailored for supervised deep learning models used in speech emotion recognition (SER). This method allows us to pinpoint the crucial acoustic features that the network heavily relies on, enabling us…

Cited by 0 Source ↗Scholar ↗