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Section: Publications & Resources

Publication: IEEE Signal Processing Letters

  Maximum-likelihood expectation-maximization (MLEM) is a widely used statistical reconstruction method in computed tomography (CT), but under ill-posed acquisition it progressively amplifies high-fre

Section: Publications & Resources

Publication: IEEE Signal Processing Letters

Variance stabilization with the generalized Anscombe transform (GAT) enables frozen Gaussian denoisers to process Poisson–Gaussian (PG) RAW noise, but its reliability depends on fitted shot/read-noise

Section: Publications & Resources

Publication: IEEE Transactions on Signal and Information Processing over Networks

In this paper, an auxiliary system method is proposed to address the predefined-time distributed constrained optimization with an event-triggered mechanism, which is applied to target monitoring in mu

Section: Publications & Resources

Publication: IEEE Transactions on Signal Processing

In decentralized optimization, gradient-tracking methods typically rely on a single global stepsize. This choice can be conservative when agents have local objectives with different smoothness constan

Section: Publications & Resources

Publication: IEEE Transactions on Image Processing

Pseudo-label self-training is a cornerstone of Source-Free Domain Adaptation (SFDA) in medical imaging, valued for improving performance while protecting data privacy. However, its effectiveness is of

Section: Publications & Resources

Publication: IEEE Transactions on Image Processing

Few-shot learning (FSL) provides a promising solution for reducing annotation cost in hyperspectral image change detection (HSI-CD). However, most existing FSL approaches focus on single-modality or h

Section: Publications & Resources

Publication: IEEE Transactions on Image Processing

Hyperspectral image (HSI) classification often suffers from the scarcity of labeled samples. Semi-supervised learning (SSL) alleviates this issue by jointly exploiting limited labeled samples and abun

Section: Publications & Resources

Publication: IEEE Transactions on Information Forensics and Security

In many secure multiparty computation (MPC) applications, the semantic domains of some operands are much smaller than the underlying arithmetic field or ring. The arithmetic domain is typically chosen

Section: Publications & Resources

Publication: IEEE Transactions on Information Forensics and Security

Dynamic Searchable Symmetric Encryption (DSSE) enables efficient searches over encrypted data but often suffers from search pattern leakage, allowing adversaries to infer sensitive information. While

Section: Publications & Resources

Publication: IEEE Transactions on Information Forensics and Security

To remove the contribution of specific data from the global model in federated learning, federated unlearning has recently emerged. Existing approaches face challenges such as reliance on full client