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03/01/2023
SMPC Task Decomposition: A Theory for Accelerating Secure Multi-party Computation Task
Today, we are in the era of big data, and data are becoming more and mor...
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12/19/2022
AI Security for Geoscience and Remote Sensing: Challenges and Future Trends
Recent advances in artificial intelligence (AI) have significantly inten...
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07/03/2022
Memory-Based Label-Text Tuning for Few-Shot Class-Incremental Learning
Few-shot class-incremental learning(FSCIL) focuses on designing learning...
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06/16/2022
Switchable Representation Learning Framework with Self-compatibility
Real-world visual search systems involve deployments on multiple platfor...
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11/19/2021
Towards Efficiently Evaluating the Robustness of Deep Neural Networks in IoT Systems: A GAN-based Method
Intelligent Internet of Things (IoT) systems based on deep neural networ...
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10/15/2021
Adversarial Purification through Representation Disentanglement
Deep learning models are vulnerable to adversarial examples and make inc...
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08/07/2021
Neighborhood Consensus Contrastive Learning for Backward-Compatible Representation
In object re-identification (ReID), the development of deep learning tec...
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06/29/2021
Inconspicuous Adversarial Patches for Fooling Image Recognition Systems on Mobile Devices
Deep learning based image recognition systems have been widely deployed ...
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02/02/2021
Recent Advances in Adversarial Training for Adversarial Robustness
Adversarial training is one of the most effective approaches defending a...
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11/03/2020
Recent Advances in Understanding Adversarial Robustness of Deep Neural Networks
Adversarial examples are inevitable on the road of pervasive application...
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09/21/2020
Feature Distillation With Guided Adversarial Contrastive Learning
Deep learning models are shown to be vulnerable to adversarial examples....
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09/21/2020
Generating Adversarial yet Inconspicuous Patches with a Single Image
Deep neural networks have been shown vulnerable toadversarial patches, w...
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02/06/2020
AI-GAN: Attack-Inspired Generation of Adversarial Examples
Adversarial examples that can fool deep models are mainly crafted by add...
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11/27/2019
Reviewing and Improving the Gaussian Mechanism for Differential Privacy
Differential privacy provides a rigorous framework to quantify data priv...
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07/11/2019
Conditional Analysis for Key-Value Data with Local Differential Privacy
Local differential privacy (LDP) has been deemed as the de facto measure...
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06/24/2015
