59 citations · 192 across the 21 of their papers we have counts for
27 papers
Towards Real-Time Temporal Graph Learning
Deniz Gurevin, Mohsin Shan, Tong Geng +3
In recent years, graph representation learning has gained significant popularity, which aims to generate node embeddings that capture features of graphs. One of the methods to achi…
Iterative Qubits Management for Quantum Index Searching in a Hybrid System
Wenrui Mu, Ying Mao, Long Cheng +3
Recent advances in quantum computing systems attract tremendous attention. Commercial companies, such as IBM, Amazon, and IonQ, have started to provide access to noisy intermediate…
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…
One Proxy Device Is Enough for Hardware-Aware Neural Architecture Search
Bingqian Lu, Jianyi Yang, Weiwen Jiang +2
Convolutional neural networks (CNNs) are used in numerous real-world applications such as vision-based autonomous driving and video content analysis. To run CNN inference on variou…
RMSMP: A Novel Deep Neural Network Quantization Framework with Row-wise Mixed Schemes and Multiple Precisions
Sung-En Chang, Yanyu Li, Mengshu Sun +4
This work proposes a novel Deep Neural Network (DNN) quantization framework, namely RMSMP, with a Row-wise Mixed-Scheme and Multi-Precision approach. Specifically, this is the firs…