Federated learning study by Chan, Aloysius Zhen Wu

“…Federated learning is a hot topic in the recent years due to the increased in emphasis for data privacy. …”
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Decentralized federated learning by Hitesh, Agarwal

“…Conventional implementations of federated learning require a centralized entity to conduct and coordinate the training with a star communication architecture. …”
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Cost of federated learning by Tan, Cheen Hao

“…Federated Learning (FL) is term coined by Google in 2016 at a time when misuse of personal data was gaining global traction. …”
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Federated learning study by Aratrika, Pal

“…We implemented different federated learning strategies such as FedAvg, FedAvgM, FedProx, FedAdam, FedYogi and FedAdagrad either from scratch or using federated learning frameworks like Secretflow or Flower, to perform federated classification on the MNIST, FashionMNIST, Cifar10 and Criteo datasets. …”
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Federated learning study by Tan, Jun Wei

“…Subsequently, employing a Federated Learning approach, the three datasets are distributed across separate clients for model training. …”
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Federated learning for image applications by Cao, Shuxin

“…For institutions or individuals to train the model together while ensuring data privacy, the concept of federated learning is proposed. In this project, we studied the aggregation algorithm FedAvg of federated learning and applied it to different models and image data. …”
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Federated learning in stock predictions by Lim, Shihao

“…The experimental results show that regardless of model parameter adjustments, the traditional LSTM method outperforms the federated LSTM method in accuracy on stock prediction.…”
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Federated graph neural network by Koh, Tat You @ Arthur

“…In this project, we implement and introduce a possible alternative means of conducting Graph Neural Network machine learning on privacy-sensitive data by combining a form of de-centralized, privacy-preserving machine learning known as Federated Learning with Graph Neural Networks. Our approach is showcased through the augmentation of the GCN and GraphSAGE GNNs with FL. …”
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Study of attacks on federated learning by Thung, Jia Cheng

“…This project will study a targeted data poisoning attack against Federated Learning, also known as label flipping attack. …”
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Peer-to-peer federated learning by Sim, Nicholas Yong Yue

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Federated learning for algorithmic trading by Aggarwal, Anusha

“…By simulating diverse market conditions through various trading and time costs across agents, this project examines the efficacy of federated learning against traditional non-federated training methodologies. …”
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Privacy-preserving federated learning (I) by Wang, Ying

“…The prediction result of Federated Learning with and without secure aggregation shows that the secure aggregation platform doesn’t affect the performance of Federated Learning.…”
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Study on attacks against federated learning by Wong, Yuan Neng

“…In this project, we aim to study the various attack and defence methodologies that can be deployed in federated learning by implementing them using an existing open-sourced federated learning implementation as the base code. …”
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Attacks on federated learning and defense strategy by Loh, Yuanchao

“…Future studies could explore how to incorporate simulations of other federated attacks and allow more diverse federated model training and analysis.…”
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Study on attacks against federated learning by Tan, Ezekiel Wei Ren

“…The increased incentive for attacking federated networks, combined with the inherent security risks associated with decentralised technologies, mean that attacks on federated networks will become more commonplace in the future. …”
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The attractiveness of the Singapore sailing federation to sponsors by Khng, Griselda

“…Interviews were conducted to identify the similarities and differences between the various international sailing federations with prestigious sponsors, to ascertain what the Singapore Sailing Federation is lacking. …”
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Homomorphic encryption(HE) enabled federated learning by Myat Nyein Soe

“…In this report, to maximise data privacy, we conducted Federated Learning algorithm with Homomorphic Encryption. …”
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Implementing and evaluating Google federated learning algorithms by Cicilia Helena

“…Amid data privacy concerns, Federated Learning(FL) has emerged as a promising machine learning paradigm that enables privacy-preserving collaborative model training. …”
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Intelligent payment system for horizontal federated learning by Ng, Randy Yi Liang

“…In this project, we aim to create a front-end interface that will allow federation initiators as well as federation participants to visualise rewards given to each participant based on varying distribution algorithms and budgets. …”
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Differential privacy in peer-to-peer federated learning by Rajkumar, Snehaa

“…The objective of this project is to study the effectiveness of differential privacy implementation on peer-to-peer federated learning in protecting proprietary data from exposure.…”
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