Lin, Yingyan

34 publications

CVPR 2025 Early-Bird Diffusion: Investigating and Leveraging Timestep-Aware Early-Bird Tickets in Diffusion Models for Efficient Training Lexington Whalen, Zhenbang Du, Haoran You, Chaojian Li, Sixu Li, Yingyan Lin

NeurIPS 2024 3D Gaussian Rendering Can Be Sparser: Efficient Rendering via Learned Fragment Pruning Zhifan Ye, Chenxi Wan, Chaojian Li, Jihoon Hong, Sixu Li, Leshu Li, Yongan Zhang, Yingyan Lin

NeurIPS 2024 AmoebaLLM: Constructing Any-Shape Large Language Models for Efficient and Instant Deployment Yonggan Fu, Zhongzhi Yu, Junwei Li, Jiayi Qian, Yongan Zhang, Xiangchi Yuan, Dachuan Shi, Roman Yakunin, Yingyan Lin

ECCV 2024 Omni-Recon: Harnessing Image-Based Rendering for General-Purpose Neural Radiance Fields Yonggan Fu, Huaizhi Qu, Zhifan Ye, Chaojian Li, Kevin Zhao, Yingyan Lin

NeurIPS 2024 Rad-NeRF: Ray-Decoupled Training of Neural Radiance Field Lidong Guo, Xuefei Ning, Yonggan Fu, Tianchen Zhao, Zhuoliang Kang, Jincheng Yu, Yingyan Lin, Yu Wang

NeurIPS 2024 ShiftAddLLM: Accelerating Pretrained LLMs via Post-Training Multiplication-Less Reparameterization Haoran You, Yipin Guo, Yichao Fu, Wei Zhou, Huihong Shi, Xiaofan Zhang, Souvik Kundu, Amir Yazdanbakhsh, Yingyan Lin

CVPR 2023 Auto-CARD: Efficient and Robust Codec Avatar Driving for Real-Time Mobile Telepresence Yonggan Fu, Yuecheng Li, Chenghui Li, Jason Saragih, Peizhao Zhang, Xiaoliang Dai, Yingyan Lin

CVPR 2023 Castling-ViT: Compressing Self-Attention via Switching Towards Linear-Angular Attention at Vision Transformer Inference Haoran You, Yunyang Xiong, Xiaoliang Dai, Bichen Wu, Peizhao Zhang, Haoqi Fan, Peter Vajda, Yingyan Lin

CVPR 2023 Hint-Aug: Drawing Hints from Foundation Vision Transformers Towards Boosted Few-Shot Parameter-Efficient Tuning Zhongzhi Yu, Shang Wu, Yonggan Fu, Shunyao Zhang, Yingyan Lin

NeurIPS 2023 ShiftAddViT: Mixture of Multiplication Primitives Towards Efficient Vision Transformer Haoran You, Huihong Shi, Yipin Guo, Yingyan Lin

ICML 2022 DepthShrinker: A New Compression Paradigm Towards Boosting Real-Hardware Efficiency of Compact Neural Networks Yonggan Fu, Haichuan Yang, Jiayi Yuan, Meng Li, Cheng Wan, Raghuraman Krishnamoorthi, Vikas Chandra, Yingyan Lin

AAAI 2022 Early-Bird GCNs: Graph-Network Co-Optimization Towards More Efficient GCN Training and Inference via Drawing Early-Bird Lottery Tickets Haoran You, Zhihan Lu, Zijian Zhou, Yonggan Fu, Yingyan Lin

ECCVW 2022 INGeo: Accelerating Instant Neural Scene Reconstruction with Noisy Geometry Priors Chaojian Li, Bichen Wu, Albert Pumarola, Peizhao Zhang, Yingyan Lin, Peter Vajda

AAAI 2022 MIA-Former: Efficient and Robust Vision Transformers via Multi-Grained Input-Adaptation Zhongzhi Yu, Yonggan Fu, Sicheng Li, Chaojian Li, Yingyan Lin

TMLR 2022 Max-Affine Spline Insights into Deep Network Pruning Haoran You, Randall Balestriero, Zhihan Lu, Yutong Kou, Huihong Shi, Shunyao Zhang, Shang Wu, Yingyan Lin, Richard Baraniuk

ICLR 2022 Patch-Fool: Are Vision Transformers Always Robust Against Adversarial Perturbations? Yonggan Fu, Shunyao Zhang, Shang Wu, Cheng Wan, Yingyan Lin

ICLR 2022 PipeGCN: Efficient Full-Graph Training of Graph Convolutional Networks with Pipelined Feature Communication Cheng Wan, Youjie Li, Cameron R. Wolfe, Anastasios Kyrillidis, Nam Sung Kim, Yingyan Lin

ICML 2022 ShiftAddNAS: Hardware-Inspired Search for More Accurate and Efficient Neural Networks Haoran You, Baopu Li, Shi Huihong, Yonggan Fu, Yingyan Lin

ECCV 2022 SuperTickets: Drawing Task-Agnostic Lottery Tickets from Supernets via Jointly Architecture Searching and Parameter Pruning Haoran You, Baopu Li, Zhanyi Sun, Xu Ouyang, Yingyan Lin

ICML 2021 Auto-NBA: Efficient and Effective Search over the Joint Space of Networks, Bitwidths, and Accelerators Yonggan Fu, Yongan Zhang, Yang Zhang, David Cox, Yingyan Lin

ICLR 2021 CPT: Efficient Deep Neural Network Training via Cyclic Precision Yonggan Fu, Han Guo, Meng Li, Xin Yang, Yining Ding, Vikas Chandra, Yingyan Lin

ICML 2021 Double-Win Quant: Aggressively Winning Robustness of Quantized Deep Neural Networks via Random Precision Training and Inference Yonggan Fu, Qixuan Yu, Meng Li, Vikas Chandra, Yingyan Lin

NeurIPS 2021 Drawing Robust Scratch Tickets: Subnetworks with Inborn Robustness Are Found Within Randomly Initialized Networks Yonggan Fu, Qixuan Yu, Yang Zhang, Shang Wu, Xu Ouyang, David Cox, Yingyan Lin

ICLR 2021 HW-NAS-Bench: Hardware-Aware Neural Architecture Search Benchmark Chaojian Li, Zhongzhi Yu, Yonggan Fu, Yongan Zhang, Yang Zhao, Haoran You, Qixuan Yu, Yue Wang, Cong Hao, Yingyan Lin

NeurIPS 2021 Locality Sensitive Teaching Zhaozhuo Xu, Beidi Chen, Chaojian Li, Weiyang Liu, Le Song, Yingyan Lin, Anshumali Shrivastava

ICCV 2021 SACoD: Sensor Algorithm Co-Design Towards Efficient CNN-Powered Intelligent PhlatCam Yonggan Fu, Yang Zhang, Yue Wang, Zhihan Lu, Vivek Boominathan, Ashok Veeraraghavan, Yingyan Lin

ICML 2020 AutoGAN-Distiller: Searching to Compress Generative Adversarial Networks Yonggan Fu, Wuyang Chen, Haotao Wang, Haoran Li, Yingyan Lin, Zhangyang Wang

ICLR 2020 Drawing Early-Bird Tickets: Toward More Efficient Training of Deep Networks Haoran You, Chaojian Li, Pengfei Xu, Yonggan Fu, Yue Wang, Xiaohan Chen, Richard G. Baraniuk, Zhangyang Wang, Yingyan Lin

NeurIPS 2020 FracTrain: Fractionally Squeezing Bit Savings Both Temporally and Spatially for Efficient DNN Training Yonggan Fu, Haoran You, Yang Zhao, Yue Wang, Chaojian Li, Kailash Gopalakrishnan, Zhangyang Wang, Yingyan Lin

AAAI 2020 Fractional Skipping: Towards Finer-Grained Dynamic CNN Inference Jianghao Shen, Yue Wang, Pengfei Xu, Yonggan Fu, Zhangyang Wang, Yingyan Lin

ECCV 2020 HALO: Hardware-Aware Learning to Optimize Chaojian Li, Tianlong Chen, Haoran You, Zhangyang Wang, Yingyan Lin

NeurIPS 2020 ShiftAddNet: A Hardware-Inspired Deep Network Haoran You, Xiaohan Chen, Yongan Zhang, Chaojian Li, Sicheng Li, Zihao Liu, Zhangyang Wang, Yingyan Lin

NeurIPS 2019 E2-Train: Training State-of-the-Art CNNs with over 80% Energy Savings Yue Wang, Ziyu Jiang, Xiaohan Chen, Pengfei Xu, Yang Zhao, Yingyan Lin, Zhangyang Wang

ICML 2018 Deep K-Means: Re-Training and Parameter Sharing with Harder Cluster Assignments for Compressing Deep Convolutions Junru Wu, Yue Wang, Zhenyu Wu, Zhangyang Wang, Ashok Veeraraghavan, Yingyan Lin