1 citations · 1 across the 3 of their papers we have counts for
3 papers
Learnable Mixed-precision and Dimension Reduction Co-design for Low-storage Activation
Yu-Shan Tai, Cheng-Yang Chang, Chieh-Fang Teng +2
Recently, deep convolutional neural networks (CNNs) have achieved many eye-catching results. However, deploying CNNs on resource-constrained edge devices is constrained by limited…
Compression-aware Projection with Greedy Dimension Reduction for Convolutional Neural Network Activations
Yu-Shan Tai, Chieh-Fang Teng, Cheng-Yang Chang +1
Convolutional neural networks (CNNs) achieve remarkable performance in a wide range of fields. However, intensive memory access of activations introduces considerable energy consum…
Task-Projected Hyperdimensional Computing for Multi-Task Learning
Cheng-Yang Chang, Yu-Chuan Chuang, An-Yeu Wu
Brain-inspired Hyperdimensional (HD) computing is an emerging technique for cognitive tasks in the field of low-power design. As a fast-learning and energy-efficient computational…