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Mingqing Xiao

mingqing_xiao AT pku.edu.cn

Ph.D. student

Peking University

Personal Site

Biography

I am currently a Ph.D. student at Peking University supervised by Prof. Zhouchen Lin. Previously I obtained my B.S. degree in computer science and technology and B.S. degree in psychology from Peking University in 2020.

Interests

  • Machine Learning
  • Computer Vision

Education

  • B.S. in Computer Science and Technology, 2016-2020

    Peking University

  • B.S. in Psychology, 2017-2020

    Peking University

Internships

 
 
 
 
 

Research Intern

Microsoft Research Asia Machine Learning Group

Sep 2019 – Jun 2020 Beijing
Worked on machine learning and computer vision.
 
 
 
 
 

Visiting Student

Johns Hopkins University CCVL Group

Jun 2019 – Sep 2019 Baltimore, US
Worked on machine learning and computer vision.

Publications @ZERO Lab

Training Much Deeper Spiking Neural Networks with a Small Number of Time-Steps. Neural Networks, 2022.

Spiking Neural Network (SNN) is a promising energy-efficient neural architecture when implemented on neuromorphic hardware. The …

Training High-Performance Low-Latency Spiking Neural Networks by Differentiation on Spike Representation. CVPR, 2022.

Spiking Neural Network (SNN) is a promising energy-efficient AI model when implemented on neuromorphic hardware. However, it is a …

Training Feedback Spiking Neural Networks by Implicit Differentiation on the Equilibrium State. NeurIPS, 2021.

Spiking neural networks (SNNs) are brain-inspired models that enable energy-efficient implementation on neuromorphic hardware. However, …

Training Neural Networks by Lifted Proximal Operator Machines. TPAMI, 2020.

We present the lifted proximal operator machine (LPOM) to train fully-connected feed-forward neural networks. LPOM represents the …

Invertible Image Rescaling. ECCV, 2020.

High-resolution digital images are usually downscaled to fit various display screens or save the cost of storage and bandwidth, …