Search Results for author: Chunxu Zhang

Found 7 papers, 2 papers with code

PromptST: Prompt-Enhanced Spatio-Temporal Multi-Attribute Prediction

no code implementations18 Sep 2023 Zijian Zhang, Xiangyu Zhao, Qidong Liu, Chunxu Zhang, Qian Ma, Wanyu Wang, Hongwei Zhao, Yiqi Wang, Zitao Liu

We devise a spatio-temporal transformer and a parameter-sharing training scheme to address the common knowledge among different spatio-temporal attributes.

Attribute

When Federated Recommendation Meets Cold-Start Problem: Separating Item Attributes and User Interactions

no code implementations22 May 2023 Chunxu Zhang, Guodong Long, Tianyi Zhou, Zijian Zhang, Peng Yan, Bo Yang

However, this separation of the recommendation model and users' private data poses a challenge in providing quality service, particularly when it comes to new items, namely cold-start recommendations in federated settings.

Attribute Federated Learning +1

Graph-guided Personalization for Federated Recommendation

no code implementations13 May 2023 Chunxu Zhang, Guodong Long, Tianyi Zhou, Peng Yan, Zijjian Zhang, Bo Yang

Federated Recommendation is a new service architecture providing recommendations without sharing user data with the server.

AutoSTL: Automated Spatio-Temporal Multi-Task Learning

no code implementations16 Apr 2023 Zijian Zhang, Xiangyu Zhao, Hao Miao, Chunxu Zhang, Hongwei Zhao, Junbo Zhang

To cope with the problems above, we propose an Automated Spatio-Temporal multi-task Learning (AutoSTL) method to handle multiple spatio-temporal tasks jointly.

Multi-Task Learning

Dual Personalization on Federated Recommendation

1 code implementation16 Jan 2023 Chunxu Zhang, Guodong Long, Tianyi Zhou, Peng Yan, Zijian Zhang, Chengqi Zhang, Bo Yang

Moreover, we provide visualizations and in-depth analysis of the personalization techniques in item embedding, which shed novel insights on the design of recommender systems in federated settings.

Privacy Preserving Recommendation Systems

Learning Optimal Data Augmentation Policies via Bayesian Optimization for Image Classification Tasks

1 code implementation6 May 2019 Chunxu Zhang, Jiaxu Cui, Bo Yang

Although we can benefit a lot from DA, designing appropriate DA policies requires a lot of expert experience and time consumption, and the evaluation of searching the optimal policies is costly.

Bayesian Optimization General Classification +5

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