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Found 6 papers, 1 papers with code
Federated Learning for Short Text Clustering
The robust short text clustering module aims to train an effective short text clustering model with local data in each client.
Learning Uniform Clusters on Hypersphere for Deep Graph-level Clustering
However, most existing graph clustering methods focus on node-level clustering, i. e., grouping nodes in a single graph into clusters.
Joint Local Relational Augmentation and Global Nash Equilibrium for Federated Learning with Non-IID Data
In server, GNE reaches an agreement among inconsistent and discrepant model deviations from clients to server, which encourages the global model to update in the direction of global optimum without breaking down the clients optimization toward their local optimums.
Robust Representation Learning with Reliable Pseudo-labels Generation via Self-Adaptive Optimal Transport for Short Text Clustering
To tackle the above issues, we propose a Robust Short Text Clustering (RSTC) model to improve robustness against imbalanced and noisy data.
Exploiting Variational Domain-Invariant User Embedding for Partially Overlapped Cross Domain Recommendation
Most of the existing CDR models assume that both the source and target domains share the same overlapped user set for knowledge transfer.
Collaborative Filtering with Attribution Alignment for Review-based Non-overlapped Cross Domain Recommendation
In this paper, we focus on the Review-based Non-overlapped Recommendation (RNCDR) problem.
