Search Results for author: Xiaoting Li

Found 8 papers, 1 papers with code

Generating In-Distribution Proxy Graphs for Explaining Graph Neural Networks

1 code implementation3 Feb 2024 Zhuomin Chen, Jiaxing Zhang, Jingchao Ni, Xiaoting Li, Yuchen Bian, Md Mezbahul Islam, Ananda Mohan Mondal, Hua Wei, Dongsheng Luo

To address it, in this paper, we propose a novel method that generates proxy graphs for explainable subgraphs that are in the distribution of training data.

Decision Making

Adversarial Collaborative Filtering for Free

no code implementations20 Aug 2023 Huiyuan Chen, Xiaoting Li, Vivian Lai, Chin-Chia Michael Yeh, Yujie Fan, Yan Zheng, Mahashweta Das, Hao Yang

In this paper, we present Sharpness-aware Collaborative Filtering (SharpCF), a simple yet effective method that conducts adversarial training without extra computational cost over the base optimizer.

Collaborative Filtering

Adversary for Social Good: Leveraging Adversarial Attacks to Protect Personal Attribute Privacy

no code implementations4 Jun 2023 Xiaoting Li, Lingwei Chen, Dinghao Wu

To address this challenge, in this paper, we leverage the inherent vulnerability of machine learning to adversarial attacks, and design a novel text-space Adversarial attack for Social Good, called Adv4SG.

Adversarial Attack Attribute

Denoising Self-attentive Sequential Recommendation

no code implementations8 Dec 2022 Huiyuan Chen, Yusan Lin, Menghai Pan, Lan Wang, Chin-Chia Michael Yeh, Xiaoting Li, Yan Zheng, Fei Wang, Hao Yang

Transformer-based sequential recommenders are very powerful for capturing both short-term and long-term sequential item dependencies.

Denoising Sequential Recommendation

TinyKG: Memory-Efficient Training Framework for Knowledge Graph Neural Recommender Systems

no code implementations8 Dec 2022 Huiyuan Chen, Xiaoting Li, Kaixiong Zhou, Xia Hu, Chin-Chia Michael Yeh, Yan Zheng, Hao Yang

We found that our TinyKG with INT2 quantization aggressively reduces the memory footprint of activation maps with $7 \times$, only with $2\%$ loss in accuracy, allowing us to deploy KGNNs on memory-constrained devices.

Knowledge Graphs Quantization +1

Towards Generating Adversarial Examples on Mixed-type Data

no code implementations17 Oct 2022 Han Xu, Menghai Pan, Zhimeng Jiang, Huiyuan Chen, Xiaoting Li, Mahashweta Das, Hao Yang

The existence of adversarial attacks (or adversarial examples) brings huge concern about the machine learning (ML) model's safety issues.

Anomaly Detection Vocal Bursts Type Prediction

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