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07/10/2023
AmadeusGPT: a natural language interface for interactive animal behavioral analysis
The process of quantifying and analyzing animal behavior involves transl...
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09/16/2022
Enhance the Visual Representation via Discrete Adversarial Training
Adversarial Training (AT), which is commonly accepted as one of the most...
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03/14/2022
Panoptic animal pose estimators are zero-shot performers
Animal pose estimation is critical in applications ranging from life sci...
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05/17/2021
Rethinking the Design Principles of Robust Vision Transformer
Recent advances on Vision Transformers (ViT) have shown that self-attent...
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03/11/2021
Adversarial Laser Beam: Effective Physical-World Attack to DNNs in a Blink
Though it is well known that the performance of deep neural networks (DN...
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03/04/2021
QAIR: Practical Query-efficient Black-Box Attacks for Image Retrieval
We study the query-based attack against image retrieval to evaluate its ...
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02/11/2020
PCNN: Pattern-based Fine-Grained Regular Pruning towards Optimizing CNN Accelerators
Weight pruning is a powerful technique to realize model compression. We ...
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11/28/2019
Light-weight Calibrator: a Separable Component for Unsupervised Domain Adaptation
Existing domain adaptation methods aim at learning features that can be ...
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07/03/2019
Non-structured DNN Weight Pruning Considered Harmful
Large deep neural network (DNN) models pose the key challenge to energy ...
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05/28/2019
Brain-inspired reverse adversarial examples
A human does not have to see all elephants to recognize an animal as an ...
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05/02/2019
Toward Extremely Low Bit and Lossless Accuracy in DNNs with Progressive ADMM
Weight quantization is one of the most important techniques of Deep Neur...
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03/29/2019
Second Rethinking of Network Pruning in the Adversarial Setting
It is well known that deep neural networks (DNNs) are vulnerable to adve...
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03/23/2019
Progressive DNN Compression: A Key to Achieve Ultra-High Weight Pruning and Quantization Rates using ADMM
Weight pruning and weight quantization are two important categories of D...
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12/31/2018
ADMM-NN: An Algorithm-Hardware Co-Design Framework of DNNs Using Alternating Direction Method of Multipliers
To facilitate efficient embedded and hardware implementations of deep ne...
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11/05/2018
A Unified Framework of DNN Weight Pruning and Weight Clustering/Quantization Using ADMM
Many model compression techniques of Deep Neural Networks (DNNs) have be...
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10/17/2018
Progressive Weight Pruning of Deep Neural Networks using ADMM
Deep neural networks (DNNs) although achieving human-level performance i...
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07/29/2018
ADAM-ADMM: A Unified, Systematic Framework of Structured Weight Pruning for DNNs
Weight pruning methods of deep neural networks (DNNs) have been demonstr...
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04/10/2018
A Systematic DNN Weight Pruning Framework using Alternating Direction Method of Multipliers
Weight pruning methods for deep neural networks (DNNs) have been investi...
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02/15/2018