Computer Vision

Stochastic Multivariate Universal-Radix Finite-State Machine: a Theoretically and Practically Elegant Nonlinear Function Approximator
Xincheng Feng, Guodong Shen, Jianhao Hu, Meng Li, Ngai Wong
Depth Shrink: Empowering Hardware-Friendly Shallow Neural Networks
Yonggan Fu, Haichuan Yang, Jiayi Yuan, Meng Li, Raghuraman Krishnamoorthi, Vikas Chandra, Yingyan Lin
Multi-Scale High-Resolution Vision Transformer for Semantic Segmentation
Jiaqi Gu, Hyoukjun Kwon, Dilin Wang, Wei Ye, Meng Li, Yu-Hsin Chen, Liangzhen Lai, Vikas Chandra, David Pan
SplitNets: Designing Neural Architectures for Efficient Distributed Computing on Head-Mounted Systems
Xin Dong, Ziyun Li, Meng Li, Zhongnan Qu, Barbara De Salvo, Chiao Liu, Hsiang-Tsung Kung
NASViT: Neural Architecture Search for Efficient Vision Transformers with Gradient Conflict aware Supernet Training
Chengyue Gong, Dilin Wang, Meng Li, Xinlei Chen, Zhicheng Yan, Yuandong Tian, Qiang Liu, Vikas Chandra
AlphaNet: Improved Training of Supernets with Alpha-Divergence
Dilin Wang, Chengyue Gong, Meng Li, Qiang Liu, Vikas Chandra
AttentiveNAS: Improving Neural Architecture Search via Attentive Sampling
Dilin Wang, Meng Li, Chengyue Gong, Vikas Chandra
Improving efficiency in neural network accelerator using operands hamming distance optimization
Meng Li, Yilei Li, Vikas Chandra
KeepAugment: A Simple Information-Preserving Data Augmentation Approach
Chengyue Gong, Dilin Wang, Meng Li, Vikas Chandra, Qiang Liu
Co-exploration of neural architectures and heterogeneous asic accelerator designs targeting multiple tasks
Lei Yang, Zheyu Yan, Meng Li, Hyoukjun Kwon, Liangzhen Lai, Tushar Krishna, Vikas Chandra, Weiwen Jiang, Yiyu Shi
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