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System Description on Automatic Simultaneous Translation Workshop
This paper shows our submission on the second automatic simultaneous translation workshop at NAACL2021.
Personalized Federated Learning via Gradient Modulation for Heterogeneous Text Summarization
To eliminate this concern, we propose a federated learning text summarization scheme, which allows users to share the global model in a cooperative learning manner without sharing raw data.
Machine Unlearning Method Based On Projection Residual
Even when data is removed from the dataset, the effects of these data persist in the model.
RL-MD: A Novel Reinforcement Learning Approach for DNA Motif Discovery
The extraction of sequence patterns from a collection of functionally linked unlabeled DNA sequences is known as DNA motif discovery, and it is a key task in computational biology.
Blur the Linguistic Boundary: Interpreting Chinese Buddhist Sutra in English via Neural Machine Translation
Buddhism is an influential religion with a long-standing history and profound philosophy.
A Privacy-Preserving Subgraph-Level Federated Graph Neural Network via Differential Privacy
Currently, the federated graph neural network (GNN) has attracted a lot of attention due to its wide applications in reality without violating the privacy regulations.
Micro-Expression Recognition Based on Attribute Information Embedding and Cross-modal Contrastive Learning
Micro-expressions have the characteristics of short duration and low intensity, and it is difficult to train a high-performance classifier with the limited number of existing micro-expressions.
FedSmart: An Auto Updating Federated Learning Optimization Mechanism
Federated learning has made an important contribution to data privacy-preserving.
