395 citations · 969 across the 46 of their papers we have counts for
7 papers · 1 filter
Characteristic Neural Ordinary Differential Equations
Xingzi Xu, Ali Hasan, Khalil Elkhalil +2
We propose Characteristic-Neural Ordinary Differential Equations (C-NODEs), a framework for extending Neural Ordinary Differential Equations (NODEs) beyond ODEs. While NODEs model…
Decentralized Multi-Target Cross-Domain Recommendation for Multi-Organization Collaborations
Enmao Diao, Vahid Tarokh, Jie Ding
Recommender Systems (RSs) are operated locally by different organizations in many realistic scenarios. If various organizations can fully share their data and perform computation i…
Assisted Learning for Organizations with Limited Imbalanced Data
Cheng Chen, Jiaying Zhou, Jie Ding +1
In the era of big data, many big organizations are integrating machine learning into their work pipelines to facilitate data analysis. However, the performance of their trained mod…
Targeted Cross-Validation
Jiawei Zhang, Jie Ding, Yuhong Yang
In many applications, we have access to the complete dataset but are only interested in the prediction of a particular region of predictor variables. A standard approach is to find…
SemiFL: Semi-Supervised Federated Learning for Unlabeled Clients with Alternate Training
Enmao Diao, Jie Ding, Vahid Tarokh
Federated Learning allows the training of machine learning models by using the computation and private data resources of many distributed clients. Most existing results on Federate…
GAL: Gradient Assisted Learning for Decentralized Multi-Organization Collaborations
Enmao Diao, Jie Ding, Vahid Tarokh
Collaborations among multiple organizations, such as financial institutions, medical centers, and retail markets in decentralized settings are crucial to providing improved service…