Time-Space Constrained Codes for Phase-Change Memories. - Minghai Qin; Eitan Yaakobi; Paul H. Siegel (GLOBECOM, 2011)

Towards minimizing read time for NAND flash. - Borja Peleato; Rajiv Agarwal; John M. Cioffi; Minghai Qin; Paul H. Siegel (GLOBECOM, 2012)

Optimized cell programming for flash memories with quantizers. - Minghai Qin; Eitan Yaakobi; Paul H. Siegel (ISIT, 2012)

WOM with retained messages. - Lele Wang 001; Minghai Qin; Eitan Yaakobi; Young-Han Kim 001; Paul H. Siegel (ISIT, 2012)

Parallel programming of rank modulation. - Minghai Qin; Anxiao Andrew Jiang; Paul H. Siegel (ISIT, 2013)

Enhanced belief propagation decoding of polar codes through concatenation. - Jing Guo; Minghai Qin; Albert Guillen i Fabregas; Paul H. Siegel (ISIT, 2014)

Lattice-Based WOM Codes for Multilevel Flash Memories. - Aman Bhatia; Minghai Qin; Aravind R. Iyengar; Brian M. Kurkoski; Paul H. Siegel (IEEE J. Sel. Areas Commun., 2014)

Constrained Codes that Mitigate Inter-Cell Interference in Read/Write Cycles for Flash Memories. - Minghai Qin; Eitan Yaakobi; Paul H. Siegel (IEEE J. Sel. Areas Commun., 2014)

Constrained Codes and Signal Processing for Non-Volatile Memories. - Minghai Qin (2014)

An alternative proof of channel polarization for channels with arbitrary input alphabets. - Jing Guo; Jossy Sayir; Minghai Qin; Albert Guillen i Fabregas (Allerton, 2015)

Balanced codes for data retention of multi-level flash memories with fast page read. - Minghai Qin; Robert Mateescu; Cyril Guyot; Zvonimir Bandic (Allerton, 2015)

Adaptive Read Thresholds for NAND Flash. - Borja Peleato; Rajiv Agarwal; John M. Cioffi; Minghai Qin; Paul H. Siegel (IEEE Trans. Commun., 2015)

Joint Source-Channel Decoding of Polar Codes for Language-Based Sources. - Ying Wang; Minghai Qin; Krishna R. Narayanan; Anxiao Jiang; Zvonimir Bandic (GLOBECOM, 2016)

Joint Source-Channel Decoding of Polar Codes for Language-Based Source. - Ying Wang; Minghai Qin; Krishna R. Narayanan; Anxiao Jiang; Zvonimir Bandic (CoRR, 2016)

Fractional Bits-Per-Cell for NAND Flash with Low Read Latency. - Minghai Qin (GLOBECOM, 2017)

Robustness of Neural Networks against Storage Media Errors. - Minghai Qin; Chao Sun; Dejan Vucinic (CoRR, 2017)

Polar Code Constructions Based on LLR Evolution. - Minghai Qin; Jing Guo; Aman Bhatia; Albert Guillen i Fabregas; Paul H. Siegel (IEEE Commun. Lett., 2017)

Low Read Latency Rewriting Codes for Multi-Level 3-D NAND Flash. - Minghai Qin; Robert Mateescu; Chao Sun; Zvonimir Bandic (IEEE Commun. Lett., 2017)

Training Recurrent Neural Networks against Noisy Computations during Inference. - Minghai Qin; Dejan Vucinic (ACSSC, 2018)

Improving Noise Tolerance of Hardware Accelerated Artificial Neural Networks. - Wen Ma; Minghai Qin; Won Ho Choi; Pi-Feng Chiu; Martin Lueker-Boden (ICMLA, 2018)

Hamming-Distance-Based Binary Representation of Numbers. - Minghai Qin (ISIT, 2018)

Noisy Computations during Inference: Harmful or Helpful? - Minghai Qin; Dejan Vucinic (CoRR, 2018)

Enhancing the Expected Lifetime of NAND Flash by Short q-Ary WOM Codes. - Bing Fan; Minghai Qin; Paul H. Siegel (IEEE Commun. Lett., 2018)

Garbage Collection Algorithms for Meta Data Updates in NAND Flash. - Minghai Qin; Robert Mateescu; Qingbo Wang; Cyril Guyot; Dejan Vucinic; Zvonimir Bandic (ICC, 2019)

Non-Volatile Memory Array Based Quantization- and Noise-Resilient LSTM Neural Networks. - Wen Ma; Pi-Feng Chiu; Won Ho Choi; Minghai Qin; Daniel Bedau; Martin Lueker-Boden (ICRC, 2019)

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 (ISCAS, 2019)

Learning in the Frequency Domain. - Kai Xu 007; Minghai Qin; Fei Sun; Yuhao Wang 002; Yen-Kuang Chen; Fengbo Ren (CVPR, 2020)

INVITED: Computation on Sparse Neural Networks and its Implications for Future Hardware. - Fei Sun; Minghai Qin; Tianyun Zhang; Liu Liu 017; Yen-Kuang Chen; Yuan Xie 001 (DAC, 2020)

A Unified DNN Weight Compression Framework Using Reweighted Optimization Methods. - Tianyun Zhang; Xiaolong Ma; Zheng Zhan 001; Shanglin Zhou; Minghai Qin; Fei Sun; Yen-Kuang Chen; Caiwen Ding; Makan Fardad; Yanzhi Wang 001 (CoRR, 2020)

Computation on Sparse Neural Networks: an Inspiration for Future Hardware. - Fei Sun; Minghai Qin; Tianyun Zhang; Liu Liu 017; Yen-Kuang Chen; Yuan Xie 001 (CoRR, 2020)

Sanity Checks for Lottery Tickets: Does Your Winning Ticket Really Win the Jackpot? - Xiaolong Ma; Geng Yuan; Xuan Shen; Tianlong Chen 001; Xuxi Chen; Xiaohan Chen 001; Ning Liu 007; Minghai Qin; Sijia Liu 001; Zhangyang Wang; Yanzhi Wang 001 (NeurIPS, 2021)

MEST: Accurate and Fast Memory-Economic Sparse Training Framework on the Edge. - Geng Yuan; Xiaolong Ma; Wei Niu 002; Zhengang Li 001; Zhenglun Kong; Ning Liu 007; Yifan Gong 004; Zheng Zhan 001; Chaoyang He 001; Qing Jin; Siyue Wang; Minghai Qin; et al. (NeurIPS, 2021)

Load-balanced Gather-scatter Patterns for Sparse Deep Neural Networks. - Fei Sun; Minghai Qin; Tianyun Zhang; Xiaolong Ma; Haoran Li; Junwen Luo; Zihao Zhao; Yen-Kuang Chen; Yuan Xie 001 (CoRR, 2021)

SPViT: Enabling Faster Vision Transformers via Soft Token Pruning. - Zhenglun Kong; Peiyan Dong; Xiaolong Ma; Xin Meng; Wei Niu 002; Mengshu Sun; Bin Ren 002; Minghai Qin; Hao Tang 005; Yanzhi Wang 001 (CoRR, 2021)

CHEX: CHannel EXploration for CNN Model Compression. - Zejiang Hou; Minghai Qin; Fei Sun; Xiaolong Ma; Kun Yuan 001; Yi Xu 008; Yen-Kuang Chen; Rong Jin 001; Yuan Xie 001; Sun-Yuan Kung (CVPR, 2022)

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 001; Yanyue Xie; Minghai Qin; Xue Lin 001; Zhenman Fang; Yanzhi Wang 001 (DAC, 2022)

Shfl-BW: accelerating deep neural network inference with tensor-core aware weight pruning. - Guyue Huang; Haoran Li; Minghai Qin; Fei Sun; Yufei Ding 001; Yuan Xie 001 (DAC, 2022)

SPViT: Enabling Faster Vision Transformers via Latency-Aware Soft Token Pruning. - Zhenglun Kong; Peiyan Dong; Xiaolong Ma; Xin Meng; Wei Niu 002; Mengshu Sun; Xuan Shen; Geng Yuan; Bin Ren 002; Hao Tang 005; Minghai Qin; Yanzhi Wang 001 (ECCV (11), 2022)

Compiler-Aware Neural Architecture Search for On-Mobile Real-time Super-Resolution. - Yushu Wu; Yifan Gong 004; Pu Zhao 001; Yanyu Li; Zheng Zhan 001; Wei Niu 002; Hao Tang 005; Minghai Qin; Bin Ren 002; Yanzhi Wang 001 (ECCV (19), 2022)

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; et al. (ECCV (12), 2022)

All-in-One: A Highly Representative DNN Pruning Framework for Edge Devices with Dynamic Power Management. - Yifan Gong 004; Zheng Zhan 001; Pu Zhao 001; Yushu Wu; Chao Wu 006; Caiwen Ding; Weiwen Jiang; Minghai Qin; Yanzhi Wang 001 (ICCAD, 2022)

Effective Model Sparsification by Scheduled Grow-and-Prune Methods. - Xiaolong Ma; Minghai Qin; Fei Sun; Zejiang Hou; Kun Yuan 001; Yi Xu 008; Yanzhi Wang 001; Yen-Kuang Chen; Rong Jin 001; Yuan Xie 001 (ICLR, 2022)

Compact Multi-level Sparse Neural Networks with Input Independent Dynamic Rerouting. - Minghai Qin; Tianyun Zhang; Fei Sun; Yen-Kuang Chen; Makan Fardad; Yanzhi Wang 001; Yuan Xie 001 (ICTAI, 2022)

Learning from the CNN-based Compressed Domain. - Zhenzhen Wang; Minghai Qin; Yen-Kuang Chen (WACV, 2022)

The Lottery Ticket Hypothesis for Vision Transformers. - Xuan Shen; Zhenglun Kong; Minghai Qin; Peiyan Dong; Geng Yuan; Xin Meng; Hao Tang 005; Xiaolong Ma; Yanzhi Wang 001 (CoRR, 2022)

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 005; Minghai Qin; Tianlong Chen 001; Xiaolong Ma; et al. (AAAI, 2023)

Towards Real-Time Segmentation on the Edge. - Yanyu Li; Changdi Yang; Pu Zhao 001; Geng Yuan; Wei Niu 002; Jiexiong Guan; Hao Tang 005; Minghai Qin; Qing Jin; Bin Ren 002; Xue Lin 001; Yanzhi Wang 001 (AAAI, 2023)

Towards High-Quality and Efficient Video Super-Resolution via Spatial-Temporal Data Overfitting. - Gen Li 012; Jie Ji; Minghai Qin; Wei Niu 002; Bin Ren 002; Fatemeh Afghah; Linke Guo; Xiaolong Ma (CVPR, 2023)

Pruning Parameterization with Bi-level Optimization for Efficient Semantic Segmentation on the Edge. - Changdi Yang; Pu Zhao 001; Yanyu Li; Wei Niu 002; Jiexiong Guan; Hao Tang 005; Minghai Qin; Bin Ren 002; Xue Lin 001; Yanzhi Wang 001 (CVPR, 2023)

Condense: A Framework for Device and Frequency Adaptive Neural Network Models on the Edge. - Yifan Gong 004; Pu Zhao 001; Zheng Zhan 001; Yushu Wu; Chao Wu 006; Zhenglun Kong; Minghai Qin; Caiwen Ding; Yanzhi Wang 001 (DAC, 2023)

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 001; Yanyue Xie; Minghai Qin; Xue Lin 001; Zhenman Fang; Yanzhi Wang 001 (DATE, 2023)

Self-Ensemble Protection: Training Checkpoints Are Good Data Protectors. - Sizhe Chen; Geng Yuan; Xinwen Cheng; Yifan Gong 004; Minghai Qin; Yanzhi Wang 001; Xiaolin Huang (ICLR, 2023)

Data Level Lottery Ticket Hypothesis for Vision Transformers. - Xuan Shen; Zhenglun Kong; Minghai Qin; Peiyan Dong; Geng Yuan; Xin Meng; Hao Tang 005; Xiaolong Ma; Yanzhi Wang 001 (IJCAI, 2023)

Data Overfitting for On-device Super-Resolution with Dynamic Algorithm and Compiler Co-design. - Gen Li 012; Zhihao Shu; Jie Ji; Minghai Qin; Fatemeh Afghah; Wei Niu 002; Xiaolong Ma (ECCV (67), 2024)

NeurRev: Train Better Sparse Neural Network Practically via Neuron Revitalization. - Gen Li 012; Lu Yin 006; Jie Ji; Wei Niu 002; Minghai Qin; Bin Ren 002; Linke Guo; Shiwei Liu 003; Xiaolong Ma (ICLR, 2024)

Advancing Dynamic Sparse Training by Exploring Optimization Opportunities. - Jie Ji; Gen Li 012; Lu Yin 006; Minghai Qin; Geng Yuan; Linke Guo; Shiwei Liu 003; Xiaolong Ma (ICML, 2024)

A Min-Max Optimization Framework for Multi-task Deep Neural Network Compression. - Jiacheng Guo; Huiming Sun; Minghai Qin; Hongkai Yu; Tianyun Zhang (ISCAS, 2024)

DISCO: Distributed Inference with Sparse Communications. - Minghai Qin; Chao Sun; Jaco Hofmann; Dejan Vucinic (WACV, 2024)

The Uniqueness of LLaMA3-70B with Per-Channel Quantization: An Empirical Study. - Minghai Qin (CoRR, 2024)

Stealthy Multi-Task Adversarial Attacks. - Jiacheng Guo; Tianyun Zhang; Lei Li; Haochen Yang; Hongkai Yu; Minghai Qin (CoRR, 2024)

An Efficient and Accurate Dynamic Sparse Training Framework Based on Parameter-Freezing. - Lei Li; Haochen Yang; Jiacheng Guo; Hongkai Yu; Minghai Qin; Tianyun Zhang (AAAI, 2025)

Robust Multi-task Adversarial Attacks Using Min-max Optimization. - Jiacheng Guo; Lei Li; Haochen Yang; Baocheng Geng; Hongkai Yu; Minghai Qin; Tianyun Zhang (ICASSP, 2025)

A min-max optimization framework for sparse multi-task deep neural network. - Jiacheng Guo; Lei Li; Huiming Sun; Minghai Qin; Hongkai Yu; Tianyun Zhang (Neurocomputing, 2025)

A unified DNN weight compression framework using reweighted optimization methods. - Mengchen Fan; Tianyun Zhang; Xiaolong Ma; Jiacheng Guo; Zheng Zhan 001; Shanglin Zhou; Minghai Qin; Caiwen Ding; Baocheng Geng; Makan Fardad; Yanzhi Wang 001 (Intell. Syst. Appl., 2025)