36 citations · 141 across the 18 of their papers we have counts for
5 papers · 1 filter
Improved Bilevel Model: Fast and Optimal Algorithm with Theoretical Guarantee
Junyi Li, Bin Gu, Heng Huang
Due to the hierarchical structure of many machine learning problems, bilevel programming is becoming more and more important recently, however, the complicated correlation between…
Privacy-Preserving Asynchronous Federated Learning Algorithms for Multi-Party Vertically Collaborative Learning
Bin Gu, An Xu, Zhouyuan Huo +2
The privacy-preserving federated learning for vertically partitioned data has shown promising results as the solution of the emerging multi-party joint modeling application, in whi…
Federated Doubly Stochastic Kernel Learning for Vertically Partitioned Data
Bin Gu, Zhiyuan Dang, Xiang Li +1
In a lot of real-world data mining and machine learning applications, data are provided by multiple providers and each maintains private records of different feature sets about com…
Faster On-Device Training Using New Federated Momentum Algorithm
Zhouyuan Huo, Qian Yang, Bin Gu +1
Mobile crowdsensing has gained significant attention in recent years and has become a critical paradigm for emerging Internet of Things applications. The sensing devices continuous…
Large Batch Training Does Not Need Warmup
Zhouyuan Huo, Bin Gu, Heng Huang
Training deep neural networks using a large batch size has shown promising results and benefits many real-world applications. However, the optimizer converges slowly at early epoch…