most citedGenetic CFL: Optimization of Hyper-Parameters in Clustered Federated Learning

66 citations · 108 across the 5 of their papers we have counts for

collaborators

5 papers

cs.IR2022★ 3 cited

ListBERT: Learning to Rank E-commerce products with Listwise BERT

Lakshya Kumar, Sagnik Sarkar

Efficient search is a critical component for an e-commerce platform with an innumerable number of products. Every day millions of users search for products pertaining to their need…

cs.IR2021

Neural Search: Learning Query and Product Representations in Fashion E-commerce

Lakshya Kumar, Sagnik Sarkar

Typical e-commerce platforms contain millions of products in the catalog. Users visit these platforms and enter search queries to retrieve their desired products. Therefore, showin…

cs.AI2021★ 66 cited

Genetic CFL: Optimization of Hyper-Parameters in Clustered Federated Learning

Shaashwat Agrawal, Sagnik Sarkar, Mamoun Alazab +3

Federated learning (FL) is a distributed model for deep learning that integrates client-server architecture, edge computing, and real-time intelligence. FL has the capability of re…

cs.CR2021★ 5 cited

Federated Learning for Intrusion Detection System: Concepts, Challenges and Future Directions

Shaashwat Agrawal, Sagnik Sarkar, Ons Aouedi +5

The rapid development of the Internet and smart devices trigger surge in network traffic making its infrastructure more complex and heterogeneous. The predominated usage of mobile…

cs.AI2021★ 34 cited

Genetically Optimized Prediction of Remaining Useful Life

Shaashwat Agrawal, Sagnik Sarkar, Gautam Srivastava +2

The application of remaining useful life (RUL) prediction has taken great importance in terms of energy optimization, cost-effectiveness, and risk mitigation. The existing RUL pred…