4.7k citations · 10.6k across the 105 of their papers we have counts for
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Learning-Accelerated ADMM for Distributed Optimal Power Flow
David Biagioni, Peter Graf, Xiangyu Zhang +3
We propose a novel data-driven method to accelerate the convergence of Alternating Direction Method of Multipliers (ADMM) for solving distributed DC optimal power flow (DC-OPF) whe…
A Case for Quantifying Statistical Robustness of Specialized Probabilistic AI Accelerators
Xiangyu Zhang, Sayan Mukherjee, Alvin R. Lebeck
Statistical machine learning often uses probabilistic algorithms, such as Markov Chain Monte Carlo (MCMC), to solve a wide range of problems. Many accelerators are proposed using s…
Testing Deep Learning Models for Image Analysis Using Object-Relevant Metamorphic Relations
Yongqiang Tian, Shiqing Ma, Ming Wen +3
Deep learning models are widely used for image analysis. While they offer high performance in terms of accuracy, people are concerned about if these models inappropriately make inf…
DetNAS: Backbone Search for Object Detection
Yukang Chen, Tong Yang, Xiangyu Zhang +3
Object detectors are usually equipped with backbone networks designed for image classification. It might be sub-optimal because of the gap between the tasks of image classification…