10 citations · 19 across the 11 of their papers we have counts for
8 papers · 1 filter
DynamicFL: Federated Learning with Dynamic Communication Resource Allocation
Qi Le, Enmao Diao, Xinran Wang +3
Federated Learning (FL) is a collaborative machine learning framework that allows multiple users to train models utilizing their local data in a distributed manner. However, consid…
Base Models for Parabolic Partial Differential Equations
Xingzi Xu, Ali Hasan, Jie Ding +1
Parabolic partial differential equations (PDEs) appear in many disciplines to model the evolution of various mathematical objects, such as probability flows, value functions in con…
ColA: Collaborative Adaptation with Gradient Learning
Enmao Diao, Qi Le, Suya Wu +4
A primary function of back-propagation is to compute both the gradient of hidden representations and parameters for optimization with gradient descent. Training large models requir…
ASCII: ASsisted Classification with Ignorance Interchange
Jiaying Zhou, Xun Xian, Na Li +1
The rapid development in data collecting devices and computation platforms produces an emerging number of agents, each equipped with a unique data modality over a particular popula…
Forecasting with Multiple Seasonality
Tianyang Xie, Jie Ding
An emerging number of modern applications involve forecasting time series data that exhibit both short-time dynamics and long-time seasonality. Specifically, time series with multi…
Assisted Learning: A Framework for Multi-Organization Learning
Xun Xian, Xinran Wang, Jie Ding +1
In an increasing number of AI scenarios, collaborations among different organizations or agents (e.g., human and robots, mobile units) are often essential to accomplish an organiza…