4 citations · 9 across the 18 of their papers we have counts for
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Coupled Data and Measurement Space Dynamics for Enhanced Diffusion Posterior Sampling
Shayan Mohajer Hamidi, En-Hui Yang, Ben Liang
Inverse problems, where the goal is to recover an unknown signal from noisy or incomplete measurements, are central to applications in medical imaging, remote sensing, and computat…
Information-Guided Diffusion Sampling for Dataset Distillation
Linfeng Ye, Shayan Mohajer Hamidi, Guang Li +3
Dataset distillation aims to create a compact dataset that retains essential information while maintaining model performance. Diffusion models (DMs) have shown promise for this tas…
Towards Undistillable Models by Minimizing Conditional Mutual Information
Linfeng Ye, Shayan Mohajer Hamidi, En-hui Yang
A deep neural network (DNN) is said to be undistillable if, when used as a black-box input-output teacher, it cannot be distilled through knowledge distillation (KD). In this case,…
Distributed Quasi-Newton Method for Fair and Fast Federated Learning
Shayan Mohajer Hamidi, Linfeng Ye
Federated learning (FL) is a promising technology that enables edge devices/clients to collaboratively and iteratively train a machine learning model under the coordination of a ce…
Coded Deep Learning: Framework and Algorithm
En-hui Yang, Shayan Mohajer Hamidi
The success of deep learning (DL) is often achieved with large models and high complexity during both training and post-training inferences, hindering training in resource-limited…
Conditional Mutual Information Based Diffusion Posterior Sampling for Solving Inverse Problems
Shayan Mohajer Hamidi, En-Hui Yang
Inverse problems are prevalent across various disciplines in science and engineering. In the field of computer vision, tasks such as inpainting, deblurring, and super-resolution ar…