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Toward Exact Convergence in Byzantine-Robust Decentralized Learning: A Statistical Identification Approach
Siyuan Zhang, Chengde Qian, Xin Liu +1
To defend against Byzantine attacks in decentralized learning, most existing methods rely on robust aggregation rules to mitigate the influence of malicious machines. However, thes…
Robust Multi-Source Domain Adaptation under Label Shift
Congbin Xu, Chengde Qian, Zhaojun Wang +1
As the volume of data continues to expand, it becomes increasingly common for data to be aggregated from multiple sources. Leveraging multiple sources for model training typically…
Changepoint Detection in Complex Models: Cross-Fitting Is Needed
Chengde Qian, Guanghui Wang, Zhaojun Wang +1
Changepoint detection is commonly formulated by minimizing the sum of in-sample losses to quantify the model's overall fit. However, for flexible modeling procedures -- especially…
Reliever: Relieving the Burden of Costly Model Fits for Changepoint Detection
Chengde Qian, Guanghui Wang, Changliang Zou
Changepoint detection typically relies on a grid-search strategy for optimal data segmentation. When model fitting itself is expensive, repeatedly fitting a model on every candidat…