7 citations · 16 across the 13 of their papers we have counts for
3 papers · 1 filter
Federated Causal Inference from Observational Data
Thanh Vinh Vo, Young lee, Tze-Yun Leong
Decentralized data sources are prevalent in real-world applications, posing a formidable challenge for causal inference. These sources cannot be consolidated into a single entity o…
Adversarial Learning Networks: Source-free Unsupervised Domain Incremental Learning
Abhinit Kumar Ambastha, Leong Tze Yun
This work presents an approach for incrementally updating deep neural network (DNN) models in a non-stationary environment. DNN models are sensitive to changes in input data distri…
An Adaptive Kernel Approach to Federated Learning of Heterogeneous Causal Effects
Thanh Vinh Vo, Arnab Bhattacharyya, Young Lee +1
We propose a new causal inference framework to learn causal effects from multiple, decentralized data sources in a federated setting. We introduce an adaptive transfer algorithm th…