257 citations · 763 across the 43 of their papers we have counts for
12 papers · 1 filter
SPViT: Enabling Faster Vision Transformers via Soft Token Pruning
Zhenglun Kong, Peiyan Dong, Xiaolong Ma +9
Recently, Vision Transformer (ViT) has continuously established new milestones in the computer vision field, while the high computation and memory cost makes its propagation in ind…
Automatic Mapping of the Best-Suited DNN Pruning Schemes for Real-Time Mobile Acceleration
Yifan Gong, Geng Yuan, Zheng Zhan +9
Weight pruning is an effective model compression technique to tackle the challenges of achieving real-time deep neural network (DNN) inference on mobile devices. However, prior pru…
MEST: Accurate and Fast Memory-Economic Sparse Training Framework on the Edge
Geng Yuan, Xiaolong Ma, Wei Niu +13
Recently, a new trend of exploring sparsity for accelerating neural network training has emerged, embracing the paradigm of training on the edge. This paper proposes a novel Memory…
Achieving on-Mobile Real-Time Super-Resolution with Neural Architecture and Pruning Search
Zheng Zhan, Yifan Gong, Pu Zhao +9
Though recent years have witnessed remarkable progress in single image super-resolution (SISR) tasks with the prosperous development of deep neural networks (DNNs), the deep learni…
Sanity Checks for Lottery Tickets: Does Your Winning Ticket Really Win the Jackpot?
Xiaolong Ma, Geng Yuan, Xuan Shen +8
There have been long-standing controversies and inconsistencies over the experiment setup and criteria for identifying the "winning ticket" in literature. To reconcile such, we rev…
Achieving Real-Time Object Detection on MobileDevices with Neural Pruning Search
Pu Zhao, Wei Niu, Geng Yuan +4
Object detection plays an important role in self-driving cars for security development. However, mobile systems on self-driving cars with limited computation resources lead to diff…
Improving DNN Fault Tolerance using Weight Pruning and Differential Crossbar Mapping for ReRAM-based Edge AI
Geng Yuan, Zhiheng Liao, Xiaolong Ma +11
Recent research demonstrated the promise of using resistive random access memory (ReRAM) as an emerging technology to perform inherently parallel analog domain in-situ matrix-vecto…
FORMS: Fine-grained Polarized ReRAM-based In-situ Computation for Mixed-signal DNN Accelerator
Geng Yuan, Payman Behnam, Zhengang Li +8
Recent works demonstrated the promise of using resistive random access memory (ReRAM) as an emerging technology to perform inherently parallel analog domain in-situ matrix-vector m…
Towards Fast and Accurate Multi-Person Pose Estimation on Mobile Devices
Xuan Shen, Geng Yuan, Wei Niu +5
The rapid development of autonomous driving, abnormal behavior detection, and behavior recognition makes an increasing demand for multi-person pose estimation-based applications, e…
A Compression-Compilation Framework for On-mobile Real-time BERT Applications
Wei Niu, Zhenglun Kong, Geng Yuan +7
Transformer-based deep learning models have increasingly demonstrated high accuracy on many natural language processing (NLP) tasks. In this paper, we propose a compression-compila…
Teachers Do More Than Teach: Compressing Image-to-Image Models
Qing Jin, Jian Ren, Oliver J. Woodford +4
Generative Adversarial Networks (GANs) have achieved huge success in generating high-fidelity images, however, they suffer from low efficiency due to tremendous computational cost…
Lottery Ticket Preserves Weight Correlation: Is It Desirable or Not?
Ning Liu, Geng Yuan, Zhengping Che +7
In deep model compression, the recent finding "Lottery Ticket Hypothesis" (LTH) (Frankle & Carbin, 2018) pointed out that there could exist a winning ticket (i.e., a properly prune…