Jingkuan Song

Patch-wise Attack for Fooling Deep Neural Network

2020 · arXiv (Cornell University)

By adding human-imperceptible noise to clean images, the resultant adversarial examples can fool other unknown models. Features of a pixel extracted by deep neural networks (DNNs) are influenced by its surrounding regions, and different DNNs …

Natural Color Fool: Towards Boosting Black-box Unrestricted Attacks

2022 · arXiv (Cornell University)

Unrestricted color attacks, which manipulate semantically meaningful color of an image, have shown their stealthiness and success in fooling both human eyes and deep neural networks. However, current works usually sacrifice the flexibility of the …

NAIS: Neural Attentive Item Similarity Model for Recommendation

2018 · IEEE Transactions on Knowledge and Data Engineering

Item-to-item collaborative filtering (aka.item-based CF) has been long used for building recommender systems in industrial settings, owing to its interpretability and efficiency in real-time personalization. It builds a user's profile as her historically interacted items, …