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06/25/2023
A Spectral Perspective towards Understanding and Improving Adversarial Robustness
Deep neural networks (DNNs) are incredibly vulnerable to crafted, imperc...
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12/24/2022
Frequency Regularization for Improving Adversarial Robustness
Deep neural networks are incredibly vulnerable to crafted, human-imperce...
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03/29/2022
Coarse to Fine: Image Restoration Boosted by Multi-Scale Low-Rank Tensor Completion
Existing low-rank tensor completion (LRTC) approaches aim at restoring a...
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03/25/2022
Deformable Butterfly: A Highly Structured and Sparse Linear Transform
We introduce a new kind of linear transform named Deformable Butterfly (...
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03/16/2022
What Do Adversarially trained Neural Networks Focus: A Fourier Domain-based Study
Although many fields have witnessed the superior performance brought abo...
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05/10/2021
Exploiting Elasticity in Tensor Ranks for Compressing Neural Networks
Elasticities in depth, width, kernel size and resolution have been explo...
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05/08/2021
EZCrop: Energy-Zoned Channels for Robust Output Pruning
Recent results have revealed an interesting observation in a trained con...
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02/15/2021
FAT: Learning Low-Bitwidth Parametric Representation via Frequency-Aware Transformation
Learning convolutional neural networks (CNNs) with low bitwidth is chall...
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02/28/2020
HOTCAKE: Higher Order Tucker Articulated Kernels for Deeper CNN Compression
The emerging edge computing has promoted immense interests in compacting...
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05/17/2019
MiSC: Mixed Strategies Crowdsourcing
Popular crowdsourcing techniques mostly focus on evaluating workers' lab...
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11/13/2018
