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2020 – today
- 2024
[j10]Zhisheng Ye
, Wei Gao, Qinghao Hu, Peng Sun, Xiaolin Wang, Yingwei Luo, Tianwei Zhang, Yonggang Wen:
Deep Learning Workload Scheduling in GPU Datacenters: A Survey. ACM Comput. Surv. 56(6): 146:1-146:38 (2024)- [j9]Liang Zhao, Qinghao Hu, Xiaoyuan Li, Jingyuan Zhao:
Multimodal Fusion Generative Adversarial Network for Image Synthesis. IEEE Signal Process. Lett. 31: 1865-1869 (2024) - [j8]Xing Lan, Jiayi Lyu, Kun Dong, Hanyu Jiang, Qinghao Hu, Jian Xue:
Does Pixel Value Represent Facial Landmark Well in Heatmap? IEEE Trans. Circuits Syst. Video Technol. 34(12): 13016-13028 (2024) - [j7]Liang Zhao, Pingda Huang, Tengtuo Chen, Chunjiang Fu, Qinghao Hu, Yangqianhui Zhang:
Multi-Sentence Complementarily Generation for Text-to-Image Synthesis. IEEE Trans. Multim. 26: 8323-8332 (2024) - [c32]Zeyu Zhu, Fanrong Li, Gang Li, Zejian Liu, Zitao Mo, Qinghao Hu, Xiaoyao Liang, Jian Cheng:
MEGA: A Memory-Efficient GNN Accelerator Exploiting Degree-Aware Mixed-Precision Quantization. HPCA 2024: 124-138 - [c31]Meng Zhang, Qinghao Hu, Cheng Wan, Haozhao Wang, Peng Sun, Yonggang Wen, Tianwei Zhang:
Sylvie: 3D-Adaptive and Universal System for Large-Scale Graph Neural Network Training. ICDE 2024: 3823-3836 - [c30]Qiaoling Chen, Qinghao Hu, Guoteng Wang, Yingtong Xiong, Ting Huang, Xun Chen, Yang Gao, Hang Yan, Yonggang Wen, Tianwei Zhang, Peng Sun:
Lins: Reducing Communication Overhead of ZeRO for Efficient LLM Training. IWQoS 2024: 1-10 - [c29]Qinghao Hu, Zhisheng Ye, Zerui Wang, Guoteng Wang, Meng Zhang, Qiaoling Chen, Peng Sun, Dahua Lin, Xiaolin Wang, Yingwei Luo, Yonggang Wen, Tianwei Zhang:
Characterization of Large Language Model Development in the Datacenter. NSDI 2024: 709-729 - [c28]Meng Zhang, Jie Sun, Qinghao Hu, Peng Sun, Zeke Wang, Yonggang Wen, Tianwei Zhang:
TorchGT: A Holistic System for Large-Scale Graph Transformer Training. SC 2024: 77 - [c27]Haozhao Wang, Yabo Jia, Meng Zhang, Qinghao Hu, Hao Ren, Peng Sun, Yonggang Wen, Tianwei Zhang:
FedDSE: Distribution-aware Sub-model Extraction for Federated Learning over Resource-constrained Devices. WWW 2024: 2902-2913 - [i26]Qiaoling Chen, Diandian Gu, Guoteng Wang, Xun Chen, YingTong Xiong, Ting Huang, Qinghao Hu, Xin Jin, Yonggang Wen, Tianwei Zhang, Peng Sun:
InternEvo: Efficient Long-sequence Large Language Model Training via Hybrid Parallelism and Redundant Sharding. CoRR abs/2401.09149 (2024) - [i25]Qinghao Hu, Zhisheng Ye, Zerui Wang, Guoteng Wang, Meng Zhang, Qiaoling Chen, Peng Sun, Dahua Lin, Xiaolin Wang, Yingwei Luo, Yonggang Wen, Tianwei Zhang:
Characterization of Large Language Model Development in the Datacenter. CoRR abs/2403.07648 (2024) - [i24]Diandian Gu, Peng Sun, Qinghao Hu, Ting Huang, Xun Chen, Yingtong Xiong, Guoteng Wang, Qiaoling Chen, Shangchun Zhao, Jiarui Fang, Yonggang Wen, Tianwei Zhang, Xin Jin, Xuanzhe Liu:
LoongTrain: Efficient Training of Long-Sequence LLMs with Head-Context Parallelism. CoRR abs/2406.18485 (2024) - [i23]Meng Zhang, Jie Sun, Qinghao Hu, Peng Sun, Zeke Wang, Yonggang Wen, Tianwei Zhang:
TorchGT: A Holistic System for Large-scale Graph Transformer Training. CoRR abs/2407.14106 (2024) - [i22]Jiangfei Duan, Shuo Zhang, Zerui Wang, Lijuan Jiang, Wenwen Qu, Qinghao Hu, Guoteng Wang, Qizhen Weng, Hang Yan, Xingcheng Zhang, Xipeng Qiu, Dahua Lin, Yonggang Wen, Xin Jin, Tianwei Zhang, Peng Sun:
Efficient Training of Large Language Models on Distributed Infrastructures: A Survey. CoRR abs/2407.20018 (2024) - [i21]Fuzhao Xue, Yukang Chen, Dacheng Li, Qinghao Hu, Ligeng Zhu, Xiuyu Li, Yunhao Fang, Haotian Tang, Shang Yang, Zhijian Liu, Ethan He, Hongxu Yin, Pavlo Molchanov, Jan Kautz, Linxi Fan, Yuke Zhu, Yao Lu, Song Han:
LongVILA: Scaling Long-Context Visual Language Models for Long Videos. CoRR abs/2408.10188 (2024) - [i20]Zeyu Zhu, Peisong Wang, Qinghao Hu, Gang Li, Xiaoyao Liang, Jian Cheng:
FastGL: A GPU-Efficient Framework for Accelerating Sampling-Based GNN Training at Large Scale. CoRR abs/2409.14939 (2024) - 2023
- [j6]Xing Lan, Qinghao Hu, Jian Cheng:
ATF: An Alternating Training Framework for Weakly Supervised Face Alignment. IEEE Trans. Multim. 25: 1798-1809 (2023) - [j5]Tianli Zhao, Qinghao Hu, Xiangyu He, Weixiang Xu, Jiaxing Wang, Cong Leng, Jian Cheng:
ECBC: Efficient Convolution via Blocked Columnizing. IEEE Trans. Neural Networks Learn. Syst. 34(1): 433-445 (2023) - [c26]Qinghao Hu, Meng Zhang, Peng Sun, Yonggang Wen, Tianwei Zhang:
Lucid: A Non-intrusive, Scalable and Interpretable Scheduler for Deep Learning Training Jobs. ASPLOS (2) 2023: 457-472 - [c25]Xinbo Chen, Sibo Hao, Yue Wang, Boyi Zhang, Haoshuang Su, Yong Cao, Di Cui, Qinghao Hu, Haoyu Wang, Mingchuan Zhou:
Master-Slave Control Strategy Applied in Microsurgical Robot. ICARM 2023: 1199-1204 - [c24]Zeyu Zhu, Fanrong Li, Zitao Mo, Qinghao Hu, Gang Li, Zejian Liu, Xiaoyao Liang, Jian Cheng:
$\rm A^2Q$: Aggregation-Aware Quantization for Graph Neural Networks. ICLR 2023 - [c23]Zhixiang Ye, Qinghao Hu, Tianli Zhao, Wangping Zhou, Jian Cheng:
MCUNeRF: Packing NeRF into an MCU with 1MB Memory. ACM Multimedia 2023: 9082-9092 - [c22]Qinghao Hu, Zhisheng Ye, Meng Zhang, Qiaoling Chen, Peng Sun, Yonggang Wen, Tianwei Zhang:
Hydro: Surrogate-Based Hyperparameter Tuning Service in Datacenters. OSDI 2023: 757-777 - [c21]Xiangyu Chen, Qinghao Hu, Kaidong Li, Cuncong Zhong, Guanghui Wang:
Accumulated Trivial Attention Matters in Vision Transformers on Small Datasets. WACV 2023: 3973-3981 - [i19]Zeyu Zhu, Fanrong Li, Zitao Mo, Qinghao Hu, Gang Li, Zejian Liu, Xiaoyao Liang, Jian Cheng:
A2Q: Aggregation-Aware Quantization for Graph Neural Networks. CoRR abs/2302.00193 (2023) - [i18]Meng Zhang, Qinghao Hu, Peng Sun, Yonggang Wen, Tianwei Zhang:
Boosting Distributed Full-graph GNN Training with Asynchronous One-bit Communication. CoRR abs/2303.01277 (2023) - [i17]Xingting Yao, Qinghao Hu, Tielong Liu, Zitao Mo, Zeyu Zhu, Zhengyang Zhuge, Jian Cheng:
Spiking NeRF: Making Bio-inspired Neural Networks See through the Real World. CoRR abs/2309.10987 (2023) - [i16]Qiaoling Chen, Qinghao Hu, Zhisheng Ye, Guoteng Wang, Peng Sun, Yonggang Wen, Tianwei Zhang:
AMSP: Super-Scaling LLM Training via Advanced Model States Partitioning. CoRR abs/2311.00257 (2023) - [i15]Zeyu Zhu, Fanrong Li, Gang Li, Zejian Liu, Zitao Mo, Qinghao Hu, Xiaoyao Liang, Jian Cheng:
MEGA: A Memory-Efficient GNN Accelerator Exploiting Degree-Aware Mixed-Precision Quantization. CoRR abs/2311.09775 (2023) - 2022
- [j4]Guan'an Wang, Qinghao Hu, Yang Yang, Jian Cheng, Zeng-Guang Hou:
Adversarial Binary Mutual Learning for Semi-Supervised Deep Hashing. IEEE Trans. Neural Networks Learn. Syst. 33(8): 4110-4124 (2022) - [c20]Qiang Chen, Qiman Wu, Jian Wang, Qinghao Hu, Tao Hu, Errui Ding, Jian Cheng, Jingdong Wang:
MixFormer: Mixing Features across Windows and Dimensions. CVPR 2022: 5239-5249 - [c19]Qinghao Hu, Gang Li, Qiman Wu, Jian Cheng:
PalQuant: Accelerating High-Precision Networks on Low-Precision Accelerators. ECCV (11) 2022: 312-327 - [c18]Qinghao Hu, Harsha Nori, Peng Sun, Yonggang Wen, Tianwei Zhang:
Primo: Practical Learning-Augmented Systems with Interpretable Models. USENIX ATC 2022: 519-538 - [i14]Weixiang Xu, Xiangyu He, Tianli Zhao, Qinghao Hu, Peisong Wang, Jian Cheng:
Soft Threshold Ternary Networks. CoRR abs/2204.01234 (2022) - [i13]Qiang Chen, Qiman Wu, Jian Wang, Qinghao Hu, Tao Hu, Errui Ding, Jian Cheng, Jingdong Wang:
MixFormer: Mixing Features across Windows and Dimensions. CoRR abs/2204.02557 (2022) - [i12]Wei Gao, Qinghao Hu, Zhisheng Ye, Peng Sun, Xiaolin Wang, Yingwei Luo, Tianwei Zhang, Yonggang Wen:
Deep Learning Workload Scheduling in GPU Datacenters: Taxonomy, Challenges and Vision. CoRR abs/2205.11913 (2022) - [i11]Qinghao Hu, Gang Li, Qiman Wu, Jian Cheng:
PalQuant: Accelerating High-precision Networks on Low-precision Accelerators. CoRR abs/2208.01944 (2022) - [i10]Xiangyu Chen, Qinghao Hu, Kaidong Li, Cuncong Zhong, Guanghui Wang:
Accumulated Trivial Attention Matters in Vision Transformers on Small Datasets. CoRR abs/2210.12333 (2022) - [i9]Yiqun Chen, Qiang Chen, Qinghao Hu, Jian Cheng:
DATE: Dual Assignment for End-to-End Fully Convolutional Object Detection. CoRR abs/2211.13859 (2022) - 2021
- [c17]Xiangyu He, Jiahao Lu, Weixiang Xu, Qinghao Hu, Peisong Wang, Jian Cheng:
Generative Zero-Shot Network Quantization. CVPR Workshops 2021: 3000-3011 - [c16]Xing Lan, Qinghao Hu, Jian Cheng:
Revisting Quantization Error in Face Alignment. ICCVW 2021: 1521-1530 - [c15]Qinghao Hu, Peng Sun, Shengen Yan, Yonggang Wen, Tianwei Zhang:
Characterization and prediction of deep learning workloads in large-scale GPU datacenters. SC 2021: 104 - [i8]Xiangyu He, Qinghao Hu, Peisong Wang, Jian Cheng:
Generative Zero-shot Network Quantization. CoRR abs/2101.08430 (2021) - [i7]Xing Lan, Qinghao Hu, Jian Cheng:
HIH: Towards More Accurate Face Alignment via Heatmap in Heatmap. CoRR abs/2104.03100 (2021) - [i6]Tianli Zhao, Qinghao Hu, Xiangyu He, Weixiang Xu, Jiaxing Wang, Cong Leng, Jian Cheng:
Architecture Aware Latency Constrained Sparse Neural Networks. CoRR abs/2109.00170 (2021) - [i5]Qinghao Hu, Peng Sun, Shengen Yan, Yonggang Wen, Tianwei Zhang:
Characterization and Prediction of Deep Learning Workloads in Large-Scale GPU Datacenters. CoRR abs/2109.01313 (2021) - 2020
- [c14]Xiangyu He, Zitao Mo, Ke Cheng, Weixiang Xu, Qinghao Hu, Peisong Wang, Qingshan Liu, Jian Cheng:
ProxyBNN: Learning Binarized Neural Networks via Proxy Matrices. ECCV (3) 2020: 223-241 - [c13]Weixiang Xu, Xiangyu He, Tianli Zhao, Qinghao Hu, Peisong Wang, Jian Cheng:
Soft Threshold Ternary Networks. IJCAI 2020: 2298-2304 - [c12]Xing Lan, Qinghao Hu, Fangzhou Xiong, Cong Leng, Jian Cheng:
ATF: Towards Robust Face Alignment via Leveraging Similarity and Diversity across Different Datasets. ACM Multimedia 2020: 2140-2148
2010 – 2019
- 2019
- [c11]Fanrong Li, Yang Zhang, Jian Cheng, Zitao Mo, Peisong Wang, Zejian Liu, Jiayun Zhang, Gang Li, Qinghao Hu, Xiangyu He, Cong Leng:
A System-Level Solution for Low-Power Object Detection. ICCV Workshops 2019: 2461-2468 - [c10]Xianyang Li, Feng Wang, Qinghao Hu, Cong Leng:
AirFace: Lightweight and Efficient Model for Face Recognition. ICCV Workshops 2019: 2678-2682 - [i4]Fanrong Li, Zitao Mo, Peisong Wang, Zejian Liu, Jiayun Zhang, Gang Li, Qinghao Hu, Xiangyu He, Cong Leng, Yang Zhang, Jian Cheng:
A System-Level Solution for Low-Power Object Detection. CoRR abs/1909.10964 (2019) - 2018
- [j3]Jian Cheng, Peisong Wang, Gang Li, Qinghao Hu, Hanqing Lu:
Recent advances in efficient computation of deep convolutional neural networks. Frontiers Inf. Technol. Electron. Eng. 19(1): 64-77 (2018) - [j2]Jian Cheng, Jiaxiang Wu, Cong Leng, Yuhang Wang, Qinghao Hu:
Quantized CNN: A Unified Approach to Accelerate and Compress Convolutional Networks. IEEE Trans. Neural Networks Learn. Syst. 29(10): 4730-4743 (2018) - [j1]Peisong Wang, Qinghao Hu, Zhiwei Fang, Chaoyang Zhao, Jian Cheng:
DeepSearch: A Fast Image Search Framework for Mobile Devices. ACM Trans. Multim. Comput. Commun. Appl. 14(1): 6:1-6:22 (2018) - [c9]Qinghao Hu, Peisong Wang, Jian Cheng:
From Hashing to CNNs: Training Binary Weight Networks via Hashing. AAAI 2018: 3247-3254 - [c8]Peisong Wang, Qinghao Hu, Yifan Zhang, Chunjie Zhang, Yang Liu, Jian Cheng:
Two-Step Quantization for Low-Bit Neural Networks. CVPR 2018: 4376-4384 - [c7]Guan'an Wang, Qinghao Hu, Jian Cheng, Zeng-Guang Hou:
Semi-supervised Generative Adversarial Hashing for Image Retrieval. ECCV (15) 2018: 491-507 - [c6]Qinghao Hu, Gang Li, Peisong Wang, Yifan Zhang, Jian Cheng:
Training Binary Weight Networks via Semi-Binary Decomposition. ECCV (13) 2018: 657-673 - [i3]Jian Cheng, Peisong Wang, Gang Li, Qinghao Hu, Hanqing Lu:
Recent Advances in Efficient Computation of Deep Convolutional Neural Networks. CoRR abs/1802.00939 (2018) - [i2]Qinghao Hu, Peisong Wang, Jian Cheng:
From Hashing to CNNs: Training BinaryWeight Networks via Hashing. CoRR abs/1802.02733 (2018) - 2017
- [c5]Qinghao Hu, Jiaxiang Wu, Lu Bai, Yifan Zhang, Jian Cheng:
Fast K-means for Large Scale Clustering. CIKM 2017: 2099-2102 - [c4]Qinghao Hu, Jiaxiang Wu, Jian Cheng, Lifang Wu, Hanqing Lu:
Pseudo Label based Unsupervised Deep Discriminative Hashing for Image Retrieval. ACM Multimedia 2017: 1584-1590 - 2016
- [c3]Jiaxiang Wu, Qinghao Hu, Cong Leng, Jian Cheng:
Shoot to Know What: An Application of Deep Networks on Mobile Devices. AAAI 2016: 4399-4400 - [c2]Jiaxiang Wu, Cong Leng, Yuhang Wang, Qinghao Hu, Jian Cheng:
Quantized Convolutional Neural Networks for Mobile Devices. CVPR 2016: 4820-4828 - 2015
- [c1]Qiang Song, Sixie Yu, Cong Leng, Jiaxiang Wu, Qinghao Hu, Jian Cheng:
Learning Deep Features For MSR-bing Information Retrieval Challenge. ACM Multimedia 2015: 169-172 - [i1]Jiaxiang Wu, Cong Leng, Yuhang Wang, Qinghao Hu, Jian Cheng:
Quantized Convolutional Neural Networks for Mobile Devices. CoRR abs/1512.06473 (2015)
Coauthor Index
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