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Found 6 papers, 2 papers with code
SeqL at SemEval-2022 Task 11: An Ensemble of Transformer Based Models for Complex Named Entity Recognition Task
This paper presents our system used to participate in task 11 (MultiCONER) of the SemEval 2022 competition.
A Payload Optimization Method for Federated Recommender Systems
We introduce the payload optimization method for federated recommender systems (FRS).
Achieving Security and Privacy in Federated Learning Systems: Survey, Research Challenges and Future Directions
In contrast with centralized ML approaches, FL saves computation to the server and does not require the clients to outsource their private data to the server.
A little goes a long way: Improving toxic language classification despite data scarcity
Detection of some types of toxic language is hampered by extreme scarcity of labeled training data.
Federated Multi-view Matrix Factorization for Personalized Recommendations
We introduce the federated multi-view matrix factorization method that extends the federated learning framework to matrix factorization with multiple data sources.
Federated Collaborative Filtering for Privacy-Preserving Personalized Recommendation System
In the Federated Learning paradigm, a master machine learning model is distributed to user clients, the clients use their locally stored data and model for both inference and calculating model updates.
