Minghai Qin
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
40
Venues
18
Active years
2011–2025
Best venue rank
A*
Where they publish
Papers
40 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | AAAI | An Efficient and Accurate Dynamic Sparse Training Framework Based on Parameter-Freezing. | Lei Li, Haochen Yang, Jiacheng Guo, Hongkai Yu, Minghai Qin, Tianyun Zhang |
| 2025 | ICASSP | Robust Multi-task Adversarial Attacks Using Min-max Optimization. | Jiacheng Guo, Lei Li, Haochen Yang, Baocheng Geng, Hongkai Yu, Minghai Qin, Tianyun Zhang |
| 2024 | ECCV | Data Overfitting for On-device Super-Resolution with Dynamic Algorithm and Compiler Co-design. | Gen Li, Zhihao Shu, Jie Ji, Minghai Qin, Fatemeh Afghah, Wei Niu, Xiaolong Ma |
| 2024 | ICLR | NeurRev: Train Better Sparse Neural Network Practically via Neuron Revitalization. | Gen Li, Lu Yin, Jie Ji, Wei Niu, Minghai Qin, Bin Ren, Linke Guo, Shiwei Liu, Xiaolong Ma |
| 2024 | ICML | Advancing Dynamic Sparse Training by Exploring Optimization Opportunities. | Jie Ji, Gen Li, Lu Yin, Minghai Qin, Geng Yuan, Linke Guo, Shiwei Liu, Xiaolong Ma |
| 2024 | ISCAS | A Min-Max Optimization Framework for Multi-task Deep Neural Network Compression. | Jiacheng Guo, Huiming Sun, Minghai Qin, Hongkai Yu, Tianyun Zhang |
| 2024 | WACV | DISCO: Distributed Inference with Sparse Communications. | Minghai Qin, Chao Sun, Jaco Hofmann, Dejan Vucinic |
| 2023 | AAAI | Peeling the Onion: Hierarchical Reduction of Data Redundancy for Efficient Vision Transformer Training. | Zhenglun Kong, Haoyu Ma, Geng Yuan, Mengshu Sun, Yanyue Xie, Peiyan Dong, Xin Meng, Xuan Shen, Hao Tang, Minghai Qin, Tianlong Chen, Xiaolong Ma, Xiaohui Xie, Zhangyang Wang, Yanzhi Wang |
| 2023 | AAAI | Towards Real-Time Segmentation on the Edge. | Yanyu Li, Changdi Yang, Pu Zhao, Geng Yuan, Wei Niu, Jiexiong Guan, Hao Tang, Minghai Qin, Qing Jin, Bin Ren, Xue Lin, Yanzhi Wang |
| 2023 | CVPR | Towards High-Quality and Efficient Video Super-Resolution via Spatial-Temporal Data Overfitting. | Gen Li, Jie Ji, Minghai Qin, Wei Niu, Bin Ren, Fatemeh Afghah, Linke Guo, Xiaolong Ma |
| 2023 | CVPR | Pruning Parameterization with Bi-level Optimization for Efficient Semantic Segmentation on the Edge. | Changdi Yang, Pu Zhao, Yanyu Li, Wei Niu, Jiexiong Guan, Hao Tang, Minghai Qin, Bin Ren, Xue Lin, Yanzhi Wang |
| 2023 | DAC | Condense: A Framework for Device and Frequency Adaptive Neural Network Models on the Edge. | Yifan Gong, Pu Zhao, Zheng Zhan, Yushu Wu, Chao Wu, Zhenglun Kong, Minghai Qin, Caiwen Ding, Yanzhi Wang |
| 2023 | DATE | ESRU: Extremely Low-Bit and Hardware-Efficient Stochastic Rounding Unit Design for Low-Bit DNN Training. | Sung-En Chang, Geng Yuan, Alec Lu, Mengshu Sun, Yanyu Li, Xiaolong Ma, Zhengang Li, Yanyue Xie, Minghai Qin, Xue Lin, Zhenman Fang, Yanzhi Wang |
| 2023 | ICLR | Self-Ensemble Protection: Training Checkpoints Are Good Data Protectors. | Sizhe Chen, Geng Yuan, Xinwen Cheng, Yifan Gong, Minghai Qin, Yanzhi Wang, Xiaolin Huang |
| 2023 | IJCAI | Data Level Lottery Ticket Hypothesis for Vision Transformers. | Xuan Shen, Zhenglun Kong, Minghai Qin, Peiyan Dong, Geng Yuan, Xin Meng, Hao Tang, Xiaolong Ma, Yanzhi Wang |
| 2022 | CVPR | CHEX: CHannel EXploration for CNN Model Compression. | Zejiang Hou, Minghai Qin, Fei Sun, Xiaolong Ma, Kun Yuan, Yi Xu, Yen-Kuang Chen, Rong Jin, Yuan Xie, Sun-Yuan Kung |
| 2022 | DAC | Hardware-efficient stochastic rounding unit design for DNN training: late breaking results. | Sung-En Chang, Geng Yuan, Alec Lu, Mengshu Sun, Yanyu Li, Xiaolong Ma, Zhengang Li, Yanyue Xie, Minghai Qin, Xue Lin, Zhenman Fang, Yanzhi Wang |
| 2022 | DAC | Shfl-BW: accelerating deep neural network inference with tensor-core aware weight pruning. | Guyue Huang, Haoran Li, Minghai Qin, Fei Sun, Yufei Ding, Yuan Xie |
| 2022 | ECCV | SPViT: Enabling Faster Vision Transformers via Latency-Aware Soft Token Pruning. | Zhenglun Kong, Peiyan Dong, Xiaolong Ma, Xin Meng, Wei Niu, Mengshu Sun, Xuan Shen, Geng Yuan, Bin Ren, Hao Tang, Minghai Qin, Yanzhi Wang |
| 2022 | ECCV | Compiler-Aware Neural Architecture Search for On-Mobile Real-time Super-Resolution. | Yushu Wu, Yifan Gong, Pu Zhao, Yanyu Li, Zheng Zhan, Wei Niu, Hao Tang, Minghai Qin, Bin Ren, Yanzhi Wang |
| 2022 | ECCV | You Already Have It: A Generator-Free Low-Precision DNN Training Framework Using Stochastic Rounding. | Geng Yuan, Sung-En Chang, Qing Jin, Alec Lu, Yanyu Li, Yushu Wu, Zhenglun Kong, Yanyue Xie, Peiyan Dong, Minghai Qin, Xiaolong Ma, Xulong Tang, Zhenman Fang, Yanzhi Wang |
| 2022 | ICCAD | All-in-One: A Highly Representative DNN Pruning Framework for Edge Devices with Dynamic Power Management. | Yifan Gong, Zheng Zhan, Pu Zhao, Yushu Wu, Chao Wu, Caiwen Ding, Weiwen Jiang, Minghai Qin, Yanzhi Wang |
| 2022 | ICLR | Effective Model Sparsification by Scheduled Grow-and-Prune Methods. | Xiaolong Ma, Minghai Qin, Fei Sun, Zejiang Hou, Kun Yuan, Yi Xu, Yanzhi Wang, Yen-Kuang Chen, Rong Jin, Yuan Xie |
| 2022 | ICTAI | Compact Multi-level Sparse Neural Networks with Input Independent Dynamic Rerouting. | Minghai Qin, Tianyun Zhang, Fei Sun, Yen-Kuang Chen, Makan Fardad, Yanzhi Wang, Yuan Xie |
| 2022 | WACV | Learning from the CNN-based Compressed Domain. | Zhenzhen Wang, Minghai Qin, Yen-Kuang Chen |
| 2020 | CVPR | Learning in the Frequency Domain. | Kai Xu, Minghai Qin, Fei Sun, Yuhao Wang, Yen-Kuang Chen, Fengbo Ren |
| 2020 | DAC | INVITED: Computation on Sparse Neural Networks and its Implications for Future Hardware. | Fei Sun, Minghai Qin, Tianyun Zhang, Liu Liu, Yen-Kuang Chen, Yuan Xie |
| 2019 | ISCAS | A Binarized Neural Network Accelerator with Differential Crosspoint Memristor Array for Energy-Efficient MAC Operations. | Pi-Feng Chiu, Won Ho Choi, Wen Ma, Minghai Qin, Martin Lueker-Boden |
| 2018 | ACSSC | Training Recurrent Neural Networks against Noisy Computations during Inference. | Minghai Qin, Dejan Vucinic |
| 2018 | ICMLA | Improving Noise Tolerance of Hardware Accelerated Artificial Neural Networks. | Wen Ma, Minghai Qin, Won Ho Choi, Pi-Feng Chiu, Martin Lueker-Boden |
| 2018 | ISIT | Hamming-Distance-Based Binary Representation of Numbers. | Minghai Qin |
| 2018 | ITA | Hamming-Distance-Based Binary Representation of Numbers. | Minghai Qin |
| 2017 | GLOBECOM | Fractional Bits-Per-Cell for NAND Flash with Low Read Latency. | Minghai Qin |
| 2016 | GLOBECOM | Joint Source-Channel Decoding of Polar Codes for Language-Based Sources. | Ying Wang, Minghai Qin, Krishna R. Narayanan, Anxiao Jiang, Zvonimir Bandic |
| 2014 | ISIT | Enhanced belief propagation decoding of polar codes through concatenation. | Jing Guo, Minghai Qin, Albert Guillen i Fabregas, Paul H. Siegel |
| 2013 | ISIT | Parallel programming of rank modulation. | Minghai Qin, Anxiao Andrew Jiang, Paul H. Siegel |
| 2012 | GLOBECOM | Towards minimizing read time for NAND flash. | Borja Peleato, Rajiv Agarwal, John M. Cioffi, Minghai Qin, Paul H. Siegel |
| 2012 | ISIT | Optimized cell programming for flash memories with quantizers. | Minghai Qin, Eitan Yaakobi, Paul H. Siegel |
| 2012 | ISIT | WOM with retained messages. | Lele Wang, Minghai Qin, Eitan Yaakobi, Young-Han Kim, Paul H. Siegel |
| 2011 | GLOBECOM | Time-Space Constrained Codes for Phase-Change Memories. | Minghai Qin, Eitan Yaakobi, Paul H. Siegel |