2 citations · 2 across the 6 of their papers we have counts for
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cs.LG2025
In-Context Compositional Learning via Sparse Coding Transformer
Wei Chen, Jingxi Yu, Zichen Miao +1
Transformer architectures have achieved remarkable success across language, vision, and multimodal tasks, and there is growing demand for them to address in-context compositional l…
cs.LG2025
Extra Clients at No Extra Cost: Overcome Data Heterogeneity in Federated Learning with Filter Decomposition
Wei Chen, Qiang Qiu
Data heterogeneity is one of the major challenges in federated learning (FL), which results in substantial client variance and slow convergence. In this study, we propose a novel s…
cs.LG2024★ 2 cited
Training Bayesian Neural Networks with Sparse Subspace Variational Inference
Junbo Li, Zichen Miao, Qiang Qiu +1
Bayesian neural networks (BNNs) offer uncertainty quantification but come with the downside of substantially increased training and inference costs. Sparse BNNs have been investiga…