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20222025
most citedJoint Local Relational Augmentation and Global Nash Equilibrium for Federated Learning with Non-IID Data

10 citations · 29 across the 19 of their papers we have counts for

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Showing 2023Show all

7 papers · 1 filter

cs.CL2023

Federated Learning for Short Text Clustering

Mengling Hu, Chaochao Chen, Weiming Liu +2

Short text clustering has been popularly studied for its significance in mining valuable insights from many short texts. In this paper, we focus on the federated short text cluster…

cs.LG2023

Learning Uniform Clusters on Hypersphere for Deep Graph-level Clustering

Mengling Hu, Chaochao Chen, Weiming Liu +3

Graph clustering has been popularly studied in recent years. However, most existing graph clustering methods focus on node-level clustering, i.e., grouping nodes in a single graph…

cs.IR2023★ 5 cited

In-processing User Constrained Dominant Sets for User-Oriented Fairness in Recommender Systems

Zhongxuan Han, Chaochao Chen, Xiaolin Zheng +4

Recommender systems are typically biased toward a small group of users, leading to severe unfairness in recommendation performance, i.e., User-Oriented Fairness (UOF) issue. The ex…

cs.LG2023★ 10 cited

Joint Local Relational Augmentation and Global Nash Equilibrium for Federated Learning with Non-IID Data

Xinting Liao, Chaochao Chen, Weiming Liu +7

Federated learning (FL) is a distributed machine learning paradigm that needs collaboration between a server and a series of clients with decentralized data. To make FL effective i…

cs.LG2023

HyperFed: Hyperbolic Prototypes Exploration with Consistent Aggregation for Non-IID Data in Federated Learning

Xinting Liao, Weiming Liu, Chaochao Chen +5

Federated learning (FL) collaboratively models user data in a decentralized way. However, in the real world, non-identical and independent data distributions (non-IID) among client…

cs.CL2023

Robust Representation Learning with Reliable Pseudo-labels Generation via Self-Adaptive Optimal Transport for Short Text Clustering

Xiaolin Zheng, Mengling Hu, Weiming Liu +2

Short text clustering is challenging since it takes imbalanced and noisy data as inputs. Existing approaches cannot solve this problem well, since (1) they are prone to obtain dege…

cs.IR2023★ 5 cited

PPGenCDR: A Stable and Robust Framework for Privacy-Preserving Cross-Domain Recommendation

Xinting Liao, Weiming Liu, Xiaolin Zheng +2

Privacy-preserving cross-domain recommendation (PPCDR) refers to preserving the privacy of users when transferring the knowledge from source domain to target domain for better perf…