Chris (Yuhao) Liu
yliu298 [at] ucsc [dot] edu
I am a MSc student in Computer Science and Engineering at
the University of
California, Santa
Cruz. I also work as a
researcher at Professor Jeffrey
Flanigan"s JLab.
My research interests broadly lie in understanding generalization in deep learning, computational
neuroscience, and the intersection of the two. My goal is to understand, to what extent, we can
leverage existing knowledge about the brain to build human-level intelligent systems.
My current research focuses on explaining the generalization behavior in deep neural networks.
Previously, I also worked on understanding the scaling law between the training data size and
the
generalization
performance of deep neural networks (aka the sample complexity rate).
Previously, I obtained my B.S. in Computer Science and
Engineering at UC Santa
Cruz.
Blog
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CV
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CV of Failure
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Email
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Github
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LinkedIn
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News
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[2022-03] I will TA CSE 20 again in Spring 2022.
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[2022-01] I will TA CSE 144 Applied Machine Learning in Winter 2022.
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[2021-09] I will serve as a teaching assistant
for CSE 20 Beginning
Programming in Python in Fall 2021.
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Research
These included publications and preprints.
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Other Projects
These include coursework and side projects.
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Sample Complexity Scaling Laws For Adversarial Training
Chris Yuhao Liu
2021
We show that adversarially training (Fast Gradient Sign Method and Projected Gradient Descent)
reduces the empirically sample complexity rate for MLP and a variety of CNN architectures on MNIST
and CIFAR-10.
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