📝 Publications
🎙 Generalization
ICLR 2023
Generalization Bounds for Federated Learning: Fast Rates, Unparticipating Clients and Unbounded Losses
Xiaolin Hu, Shaojie Li, Yong Liu
- This paper provides a theoretical analysis of generalization error of federated learning.
- We assume that the heterogeneous clients are sampled from a meta-distribution. In this framework, we characterize the generalization error for unparticipating clients.
- We further derive convergence bounds for heavy-tail losses.
🧬 AI+Science
APMC 2020
A Deep Learning Framework for Solving Rectangular Waveguide Problems
Xiaolin Hu, Nicholas E. Buri, APMC 2020 (Oral) |
- We employ Physics Informed Neural Networks (PINNs) to solve rectangular waveguide problems.
- We successfully apply PINNs to the task of solving electric and magnetic fields, which can be described by partial differential equations (PDEs).
- We also show the applicability of the framework for predicting the unknown parameters such as wavenumber.
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APMC 2019
Capacity Estimation of MIMO Systems via Support Vector Regression
Xiaolin Hu, Nicholas E. Buri, APMC 2019 (Oral) -
APMC 2020
Multiple Signal DoA Estimation with Unknown Electromagnetic Coupling using Gaussian Process
Qifeng Wang, Nicholas E. Buris, Xiaolin Hu, APMC 2020
🧑🎨 Generative Model
ICIP 2021
3D Grid Transformation Network For Point Cloud Completion
Xiaobao Deng, Xiaolin Hu, Nicholas E. Buris, Ping An, Yilei Chen, ICIP 2021
🚍 Others
- Wavelength-tunable Q-switched fiber laser based on a 45 tilted fiber grating
Xiaolin Hu, Zhijun Yan, Qianqian Huang, Chuanhang Zou, Tianxing Wang, Chengbo Mou, Opto-Electronic Engineering 2018