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Found 5 papers, 1 papers with code
ListBERT: Learning to Rank E-commerce products with Listwise BERT
Our experiments indicate that the RoBERTa model fine-tuned with an NDCG based surrogate loss function(approxNDCG) achieves an NDCG improvement of 13. 9% compared to other popular listwise loss functions like ListNET and ListMLE.
Neural Search: Learning Query and Product Representations in Fashion E-commerce
For the product retrieval task, RoBERTa model is able to outperform other two models with an improvement of 164. 7% in Precision@50 and 145. 3% in Recall@50.
Genetic CFL: Optimization of Hyper-Parameters in Clustered Federated Learning
Federated learning (FL) is a distributed model for deep learning that integrates client-server architecture, edge computing, and real-time intelligence.
Federated Learning for Intrusion Detection System: Concepts, Challenges and Future Directions
The paper finally presents the plausible solutions associated with the identified challenges in FL based intrusion detection system implementation acting as a baseline for prospective research.
Genetically Optimized Prediction of Remaining Useful Life
The application of remaining useful life (RUL) prediction has taken great importance in terms of energy optimization, cost-effectiveness, and risk mitigation.
