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05/25/2023
DiffusionShield: A Watermark for Copyright Protection against Generative Diffusion Models
Recently, Generative Diffusion Models (GDMs) have showcased their remark...
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05/24/2023
Sharpness-Aware Data Poisoning Attack
Recent research has highlighted the vulnerability of Deep Neural Network...
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10/18/2022
Transferable Unlearnable Examples
With more people publishing their personal data online, unauthorized dat...
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10/18/2022
Towards Fair Classification against Poisoning Attacks
Fair classification aims to stress the classification models to achieve ...
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10/17/2022
Probabilistic Categorical Adversarial Attack Adversarial Training
The existence of adversarial examples brings huge concern for people to ...
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09/21/2022
Seen to Unseen: When Fuzzy Inference System Predicts IoT Device Positioning Labels That Had Not Appeared in Training Phase
Situating at the core of Artificial Intelligence (AI), Machine Learning ...
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09/21/2022
A Comprehensive Survey on Trustworthy Recommender Systems
As one of the most successful AI-powered applications, recommender syste...
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06/26/2022
A Pre-Computing Solution for Online Advertising Serving
Click-Through Rate (CTR) prediction plays a key role in online advertisi...
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06/01/2022
Defense Against Gradient Leakage Attacks via Learning to Obscure Data
Federated learning is considered as an effective privacy-preserving lear...
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05/12/2022
Direct Foundations for Compositional Programming
The recently proposed CP language adopts Compositional Programming: a ne...
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05/02/2022
Enhancing Adversarial Training with Feature Separability
Deep Neural Network (DNN) are vulnerable to adversarial attacks. As a co...
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04/21/2022
Color Invariant Skin Segmentation
This paper addresses the problem of automatically detecting human skin i...
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04/03/2022
Virtual Relational Knowledge Graphs for Recommendation
Incorporating knowledge graph as side information has become a new trend...
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08/07/2021
Jointly Attacking Graph Neural Network and its Explanations
Graph Neural Networks (GNNs) have boosted the performance for many graph...
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07/28/2021
Imbalanced Adversarial Training with Reweighting
Adversarial training has been empirically proven to be one of the most e...
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06/14/2021
Pre-Trained Models: Past, Present and Future
Large-scale pre-trained models (PTMs) such as BERT and GPT have recently...
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06/09/2021
Towards the Memorization Effect of Neural Networks in Adversarial Training
Recent studies suggest that “memorization” is one important factor for o...
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05/06/2021
Analytical Differential Calculus with Integration
Differential lambda-calculus was first introduced by Thomas Ehrhard and ...
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10/13/2020
To be Robust or to be Fair: Towards Fairness in Adversarial Training
Adversarial training algorithms have been proven to be reliable to impro...
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09/02/2020
Yet Meta Learning Can Adapt Fast, It Can Also Break Easily
Meta learning algorithms have been widely applied in many tasks for effi...
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05/13/2020
DeepRobust: A PyTorch Library for Adversarial Attacks and Defenses
DeepRobust is a PyTorch adversarial learning library which aims to build...
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03/02/2020
Adversarial Attacks and Defenses on Graphs: A Review and Empirical Study
Deep neural networks (DNNs) have achieved significant performance in var...
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11/29/2019
Collaborative Attention Network for Person Re-identification
Jointly utilizing global and local features to improve model accuracy is...
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09/17/2019
Adversarial Attacks and Defenses in Images, Graphs and Text: A Review
Deep neural networks (DNN) have achieved unprecedented success in numero...
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05/17/2018
