Publications
My research spans reinforcement learning, robotics, efficient AI systems, neural architecture search, optimization, computer vision, and statistical machine learning.
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Conference Papers
Siqi Guo, Ming Lin, Tianbao Yang. DRTriton: Large-Scale Synthetic Data Driven Reinforcement Learning for Triton Kernel Generation. Conference on Neural Information Processing Systems (NeurIPS), 2026.
arXiv · GitHub
Gang Li, Yan Chen, Ming Lin, Tianbao Yang. DRPO: Efficient Reasoning via Decoupled Reward Policy Optimization. International Conference on Learning Representations (ICLR), 2026.
arXiv · GitHub
Gang Li, Ming Lin, Tomer Galanti, Zhengzhong Tu, Tianbao Yang. DisCO: Reinforcing Large Reasoning Models with Discriminative Constrained Optimization. Conference on Neural Information Processing Systems (NeurIPS), 2025.
arXiv · Article · GitHub
Youpeng Zhao, Ming Lin, Huadong Tang, Qiang Wu, Jun Wang. MeRino: Entropy-Driven Design for Generative Language Models on IoT Devices. AAAI Conference on Artificial Intelligence (AAAI), 2025.
arXiv · Article
Xiyuan Wei, Ming Lin, Fanjiang Ye, Fengguang Song, Liangliang Cao, My T. Thai, Tianbao Yang. Model Steering: Learning with a Reference Model Improves Generalization Bounds and Scaling Laws. International Conference on Machine Learning (ICML), 2025.
arXiv · Article
Xuan Shen, Pu Zhao, Yifan Gong, Zhenglun Kong, Zheng Zhan, Yushu Wu, Ming Lin, Chao Wu, Xue Lin, Yanzhi Wang. Search for Efficient Large Language Models. Conference on Neural Information Processing Systems (NeurIPS), 2024.
arXiv · Article · GitHub
Xuan Shen, Peiyan Dong, Lei Lu, Zhenglun Kong, Zhengang Li, Ming Lin, Chao Wu, Yanzhi Wang. Agile-Quant: Activation-Guided Quantization for Faster Inference of LLMs on the Edge. AAAI Conference on Artificial Intelligence (AAAI), 2024.
arXiv · Article
Xuan Shen, Yaohua Wang, Ming Lin, Yilun Huang, Hao Tang, Xiuyu Sun, Yanzhi Wang. DeepMAD: Mathematical Architecture Design for Deep Convolutional Neural Network. IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
arXiv · Article · GitHub
Junyan Wang, Zhenhong Sun, Yichen Qian, Dong Gong, Xiuyu Sun, Ming Lin, Maurice Pagnucco, Yang Song. Maximizing Spatio-Temporal Entropy of Deep 3D CNNs for Efficient Video Recognition. International Conference on Learning Representations (ICLR), 2023.
Article
Shuning Chang, Pichao Wang, Ming Lin, Fan Wang, David Junhao Zhang, Rong Jin, Mike Zheng Shou. Making Vision Transformers Efficient from a Token Sparsification View. IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
arXiv · Article
Zhenhong Sun, Ce Ge, Junyan Wang, Ming Lin, Hesen Chen, Hao Li, Xiuyu Sun. Entropy-Driven Mixed-Precision Quantization for Deep Network Design on IoT Devices. Conference on Neural Information Processing Systems (NeurIPS), 2022.
Article
Zhenhong Sun, Ming Lin, Xiuyu Sun, Zhiyu Tan, Hao Li, Rong Jin. MAE-DET: Revisiting Maximum Entropy Principle in Zero-Shot NAS for Efficient Object Detection. International Conference on Machine Learning (ICML), 2022.
arXiv · Article · GitHub · BibTeX
Yiqi Jiang, Zhiyu Tan, Junyan Wang, Xiuyu Sun, Ming Lin, Hao Li. GiraffeDet: A Heavy-Neck Paradigm for Object Detection. International Conference on Learning Representations (ICLR), 2022.
Article · GitHub · BibTeX
Yaohua Wang, Fangyi Zhang, Ming Lin, Senzhang Wang, Xiuyu Sun, Rong Jin. Robust Graph Structure Learning over Images via Multiple Statistical Tests. Conference on Neural Information Processing Systems (NeurIPS), 2022.
Article · BibTeX
Pichao Wang, Xue Wang, Fan Wang, Ming Lin, Shuning Chang, Hao Li, Rong Jin. KVT: k-NN Attention for Boosting Vision Transformers. European Conference on Computer Vision (ECCV), 2022.
Article · GitHub · BibTeX
Yichen Qian, Xiuyu Sun, Ming Lin, Zhiyu Tan, Rong Jin. Entroformer: A Transformer-Based Entropy Model for Learned Image Compression. International Conference on Learning Representations (ICLR), 2022.
Article · GitHub · BibTeX
Yaohua Wang, Yaobin Zhang, Fangyi Zhang, Senzhang Wang, Ming Lin, YuQi Zhang, Xiuyu Sun. Ada-NETS: Face Clustering via Adaptive Neighbour Discovery in the Structure Space. International Conference on Learning Representations (ICLR), 2022.
Article · GitHub · BibTeX
Yichen Qian, Zhiyu Tan, Xiuyu Sun, Ming Lin, Dongyang Li, Zhenhong Sun, Hao Li, Rong Jin. Learning Accurate Entropy Model with Global Reference for Image Compression. International Conference on Learning Representations (ICLR), 2021.
Article · BibTeX
Ming Lin, Pichao Wang, Zhenhong Sun, Hesen Chen, Xiuyu Sun, Qi Qian, Hao Li, Rong Jin. Zen-NAS: A Zero-Shot NAS for High-Performance Image Recognition. IEEE/CVF International Conference on Computer Vision (ICCV), 2021.
arXiv · Article · GitHub · BibTeX
Ming Lin, Xiaomin Song, Qi Qian, Hao Li, Liang Sun, Shenghuo Zhu, Rong Jin. Robust Gaussian Process Regression for Real-Time High-Precision GPS Signal Enhancement. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2019.
arXiv · Article · BibTeX
Hesen Chen, Ming Lin, Xiuyu Sun, Qi Qian, Hao Li, Rong Jin. MuffNet: Multi-Layer Feature Federation for Mobile Deep Learning. IEEE/CVF International Conference on Computer Vision Workshops (ICCVW), 2019.
Article · BibTeX
Ming Lin, Shuang Qiu, Jieping Ye, Xiaomin Song, Qi Qian, Liang Sun, Shenghuo Zhu, Rong Jin. Which Factorization Machine Modeling Is Better: A Theoretical Answer with Optimal Guarantee. AAAI Conference on Artificial Intelligence (AAAI), 2019.
arXiv · Article · BibTeX
Tieliang Gong, Guangtao Wang, Jieping Ye, Zongben Xu, Ming Lin. Margin-Based PU Learning. AAAI Conference on Artificial Intelligence (AAAI), 2018.
Article · Appendix · BibTeX
Xiang Li, Aoxiao Zhong, Ming Lin, Ning Guo, Mu Sun, Arkadiusz Sitek, Jieping Ye, James Thrall, Quanzheng Li. Self-Paced Convolutional Neural Network for Computer-Aided Detection in Medical Imaging Analysis. International Workshop on Machine Learning in Medical Imaging (MLMI), 2017.
arXiv · Article · BibTeX
Zhenzhong Lan, Shoou-I Yu, Dezhong Yao, Ming Lin, Bhiksha Raj, Alexander G. Hauptmann. The Best of Both Worlds: Combining Data-Independent and Data-Driven Approaches for Action Recognition. IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2016.
arXiv · Article · BibTeX
Ming Lin, Jieping Ye. A Non-Convex One-Pass Framework for Generalized Factorization Machine and Rank-One Matrix Sensing. Conference on Neural Information Processing Systems (NeurIPS), 2016.
arXiv · Article · GitHub · BibTeX
Chuang Gan, Ming Lin, Yi Yang, Gerard de Melo, Alexander G. Hauptmann. Concepts Not Alone: Exploring Pairwise Relationships for Zero-Shot Video Activity Recognition. AAAI Conference on Artificial Intelligence (AAAI), 2016.
Article · BibTeX
Chuang Gan, Ming Lin, Yi Yang, Alexander G. Hauptmann. Exploring Semantic Inter-Class Relationships for Zero-Shot Action Recognition. AAAI Conference on Artificial Intelligence (AAAI), 2015.
Article · BibTeX
Zhenzhong Lan, Ming Lin, Xuanchong Li, Alexander G. Hauptmann, Bhiksha Raj. Beyond Gaussian Pyramid: Multi-Skip Feature Stacking for Action Recognition. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015.
arXiv · Article · BibTeX
Ming Lin, Zhenzhong Lan, Alexander G. Hauptmann. Density-Corrected Sparse Recovery When the R.I.P. Condition Is Broken. International Joint Conference on Artificial Intelligence (IJCAI), 2015.
Article · BibTeX
Shoou-I Yu, Lu Jiang, Zexi Mao, Xiaojun Chang, Xingzhong Du, Chuang Gan, Zhenzhong Lan, Zhongwen Xu, Xuanchong Li, Yang Cai, Anurag Kumar, Yajie Miao, Lara Martin, Nikolas Wolfe, Shicheng Xu, Huan Li, Ming Lin, Zhigang Ma, Yi Yang, Deyu Meng, Shiguang Shan, Pinar Duygulu Sahin, Susanne Burger, Florian Metze, Rita Singh, Bhiksha Raj, Teruko Mitamura, Richard Stern, Alexander G. Hauptmann. Informedia@TRECVID 2014 MED and MER. NIST TRECVID Video Retrieval Evaluation Workshop (TRECVID), 2014.
Article · BibTeX
Ming Lin, Rong Jin, Changshui Zhang. Efficient Sparse Recovery via Adaptive Non-Convex Regularizers with Oracle Property. Conference on Uncertainty in Artificial Intelligence (UAI), 2014.
Article · Appendix · BibTeX
Lijun Zhang, Jinfeng Yi, Rong Jin, Ming Lin, Xiaofei He. Online Kernel Learning with a Near-Optimal Sparsity Bound. International Conference on Machine Learning (ICML), 2013.
Article · BibTeX
Journal Papers
Guihong Li, Duc Hoang, Kartikeya Bhardwaj, Ming Lin, Zhangyang Wang, Radu Marculescu. Zero-Shot Neural Architecture Search: Challenges, Solutions, and Opportunities. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
arXiv · Article
Jian Liang, Kun Chen, Ming Lin, Changshui Zhang, Fei Wang. Robust Finite Mixture Regression for Heterogeneous Targets. Data Mining and Knowledge Discovery, 2018.
arXiv · BibTeX
Ming Lin, Pinghua Gong, Tao Yang, Jieping Ye, Roger L. Albin, Hiroko H. Dodge. Big Data Analytical Approaches to the NACC Dataset: Aiding Preclinical Trial Enrichment. Alzheimer Disease and Associated Disorders, 2018.
Article · BibTeX
Daqing Chang, Ming Lin, Changshui Zhang. On the Generalization Ability of Online Gradient Descent Algorithm Under the Quadratic Growth Condition. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2018.
Article · BibTeX
Ming Lin, Vaibhav Narayan, Wayne C. Drevets, Jieping Ye, Qingqin Li. Application of Growth Mixture Modeling in Antidepressant Treatment Response Studies. Biological Psychiatry, 2017.
Article · RIS
Xiaojun Chang, Zhigang Ma, Ming Lin, Yi Yang, Alexander G. Hauptmann. Feature Interaction Augmented Sparse Learning for Fast Kinect Motion Detection. IEEE Transactions on Image Processing (TIP), 2017.
Article · BibTeX
Shoou-I Yu, Yi Yang, Zhongwen Xu, Shicheng Xu, Deyu Meng, Zexi Mao, Zhigang Ma, Ming Lin, Xuanchong Li, Huan Li, Zhenzhong Lan, Lu Jiang, Alexander G. Hauptmann, Chuang Gan, Xingzhong Du, Xiaojun Chang. Strategies for Searching Video Content with Text Queries or Video Examples. ITE Transactions on Media Technology and Applications, 2016.
arXiv · Article · BibTeX
Ming Lin, Lijun Zhang, Rong Jin, Shifeng Weng, Changshui Zhang. Online Kernel Learning with Nearly Constant Support Vectors. Neurocomputing, 2016.
Article · BibTeX
Zheng Hu, Ming Lin, Changshui Zhang. Dependent Online Kernel Learning with a Constant Number of Random Fourier Features. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2015.
Article · BibTeX
Zheng Pan, Ming Lin, Guangdong Hou, Changshui Zhang. Damping Proximal Coordinate Descent Algorithm for Non-Convex Regularization. Neurocomputing, 2015.
Article · BibTeX
Ming Lin, Fei Wang, Changshui Zhang. Large-Scale Eigenvector Approximation via Hilbert Space Embedding Nyström. Pattern Recognition (PR), 2015.
Article · BibTeX
Ming Lin, Shifeng Weng, Changshui Zhang. On the Sample Complexity of Random Fourier Features for Online Learning: How Many Random Fourier Features Do We Need? ACM Transactions on Knowledge Discovery from Data (TKDD), 2014.
Article · BibTeX
Shizhun Yang, Ming Lin, Chenping Hou, Changshui Zhang, Yi Wu. A General Framework for Transfer Sparse Subspace Learning. Neural Computing and Applications, 2012.
Article · RIS
Preprints
Ming Lin, Hesen Chen, Xiuyu Sun, Qi Qian, Hao Li, Rong Jin. Neural Architecture Design for GPU-Efficient Networks. arXiv preprint, 2020.
arXiv · GitHub
Yonathan Aflalo, Asaf Noy, Ming Lin, Itamar Friedman, Lihi Zelnik. Knapsack Pruning with Inner Distillation. arXiv preprint, 2020.
arXiv · GitHub
Yi Xu, Asaf Noy, Ming Lin, Qi Qian, Hao Li, Rong Jin. WeMix: How to Better Utilize Data Augmentation. arXiv preprint, 2020.
arXiv
Shuang Qiu, Tingjin Luo, Jieping Ye, Ming Lin. Nonconvex One-Bit Single-Label Multi-Label Learning. arXiv preprint, 2017.
arXiv
Ming Lin, Shuang Qiu, Bin Hong, Jieping Ye. The Second-Order Linear Model. arXiv preprint, 2017.
arXiv · GitHub
Zhenzhong Lan, Xuanchong Li, Ming Lin, Alexander G. Hauptmann. Long-Short-Term Motion Feature for Action Classification and Retrieval. arXiv preprint, 2015.
arXiv
Zhenzhong Lan, Shoou-I Yu, Ming Lin, Bhiksha Raj, Alexander G. Hauptmann. Handcrafted Local Features Are Convolutional Neural Networks. arXiv preprint, 2015.
arXiv