no code implementations • 15 Apr 2024 • Jaeyeon Jang, Diego Klabjan, Veena Mendiratta, Fanfei Meng
Federated learning is an emerging paradigm for decentralized training of machine learning models on distributed clients, without revealing the data to the central server.
no code implementations • 11 Feb 2024 • Fanfei Meng, Chen-Ao Wang, LeLe Zhang
The paper provides a comprehensive overview of Neural Architecture Search (NAS), emphasizing its evolution from manual design to automated, computationally-driven approaches.
no code implementations • 5 Dec 2023 • Fanfei Meng, LeLe Zhang, Yu Chen, Yuxin Wang
Transformer requires a fixed number of layers and heads which makes them inflexible to the complexity of individual samples and expensive in training and inference.
no code implementations • 30 Nov 2023 • Fanfei Meng, Yuxin Wang, LeLe Zhang, Yingxin Zhao
This paper first introduces three common logical circuit decision criteria in hard decisions and analyzes their decision rigor.
no code implementations • 30 Nov 2023 • Yuxin Wang, Fanfei Meng, Xiaotian Wang, Chaoyu Xie
Due to the necessary security for the airport and flight, passengers are required to have strict security check before getting aboard.
no code implementations • 30 Nov 2023 • Fanfei Meng, LeLe Zhang, Yu Chen, Yuxin Wang
Federated learning (FL) is an emerging paradigm for decentralized training of machine learning models on distributed clients, without revealing the data to the central server.
no code implementations • 23 Oct 2023 • Fanfei Meng, Chen-Ao Wang
We propose a novel framework based on the attention mechanism to identify the sentiment of a movie review document.
no code implementations • 21 Oct 2021 • Fanfei Meng, Lalita Jagadeesan, Marina Thottan
Microservice-based architectures enable different aspects of web applications to be created and updated independently, even after deployment.