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A Survey on Soft Computing Techniques for Federated Learning- Applications, Challenges and Future Directions
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Outgoing claims: the papers this work cites, builds on, or argues with.
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CMFL: Mitigating Communication Overhead for Federated Learning
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Federated Learning Versus Classical Machine Learning: A Convergence Comparison
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Artificial Neural Networks
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Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding
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Federated Learning: Strategies for Improving Communication Efficiency
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Federated Learning Of Out-Of-Vocabulary Words
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On Soft Computing Techniques in Various Areas
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