87 citations · 147 across the 10 of their papers we have counts for
10 papers
The Larger The Fairer? Small Neural Networks Can Achieve Fairness for Edge Devices
Yi Sheng, Junhuan Yang, Yawen Wu +5
Along with the progress of AI democratization, neural networks are being deployed more frequently in edge devices for a wide range of applications. Fairness concerns gradually emer…
Automated Architecture Search for Brain-inspired Hyperdimensional Computing
Junhuan Yang, Yi Sheng, Sizhe Zhang +6
This paper represents the first effort to explore an automated architecture search for hyperdimensional computing (HDC), a type of brain-inspired neural network. Currently, HDC des…
BSC: Block-based Stochastic Computing to Enable Accurate and Efficient TinyML
Yuhong Song, Edwin Hsing-Mean Sha, Qingfeng Zhuge +4
Along with the progress of AI democratization, machine learning (ML) has been successfully applied to edge applications, such as smart phones and automated driving. Nowadays, more…
Can Noise on Qubits Be Learned in Quantum Neural Network? A Case Study on QuantumFlow
Zhiding Liang, Zhepeng Wang, Junhuan Yang +4
In the noisy intermediate-scale quantum (NISQ) era, one of the key questions is how to deal with the high noise level existing in physical quantum bits (qubits). Quantum error corr…
Standing on the Shoulders of Giants: Hardware and Neural Architecture Co-Search with Hot Start
Weiwen Jiang, Lei Yang, Sakyasingha Dasgupta +2
Hardware and neural architecture co-search that automatically generates Artificial Intelligence (AI) solutions from a given dataset is promising to promote AI democratization; howe…
Co-Exploration of Neural Architectures and Heterogeneous ASIC Accelerator Designs Targeting Multiple Tasks
Lei Yang, Zheyu Yan, Meng Li +6
Neural Architecture Search (NAS) has demonstrated its power on various AI accelerating platforms such as Field Programmable Gate Arrays (FPGAs) and Graphic Processing Units (GPUs).…