Ming Lin - RankMe

70 papers A* 20A 1Journal 42Unranked 7

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Beyond Test-Time Training: Learning to Reason via Hardware-Efficient Optimal Control. CoRR Peihao Wang, Shan Yang, Xijun Wang, Tesi Xiao, Xin Liu, Changlong Yu, Yu Lou, Pan Li, Zhangyang Wang, Ming Lin, René Vidal
2025	J	`jnl`	DRPO: Efficient Reasoning via Decoupled Reward Policy Optimization. CoRR Gang Li, Yan Chen, Ming Lin, Tianbao Yang
2025	J	`jnl`	DisCO: Reinforcing Large Reasoning Models with Discriminative Constrained Optimization. CoRR Gang Li, Ming Lin, Tomer Galanti, Zhengzhong Tu, Tianbao Yang
2025	A*	`conf`	Model Steering: Learning with a Reference Model Improves Generalization Bounds and Scaling Laws. ICML Xiyuan Wei, Ming Lin, Fanjiang Ye, Fengguang Song, Liangliang Cao, My T. Thai, Tianbao Yang
2025	J	`jnl`	Model Steering: Learning with a Reference Model Improves Generalization Bounds and Scaling Laws. CoRR Xiyuan Wei, Ming Lin, Fanjiang Ye, Fengguang Song, Liangliang Cao, My T. Thai, Tianbao Yang
2024	A*	`conf`	Agile-Quant: Activation-Guided Quantization for Faster Inference of LLMs on the Edge. AAAI Xuan Shen, Peiyan Dong, Lei Lu, Zhenglun Kong, Zhengang Li, Ming Lin, Chao Wu, Yanzhi Wang
2024	A*	`conf`	Search for Efficient Large Language Models. NeurIPS Xuan Shen, Pu Zhao, Yifan Gong, Zhenglun Kong, Zheng Zhan, Yushu Wu, Ming Lin, Chao Wu, Xue Lin, Yanzhi Wang
2024	J	`jnl`	Search for Efficient Large Language Models. CoRR Xuan Shen, Pu Zhao, Yifan Gong, Zhenglun Kong, Zheng Zhan, Yushu Wu, Ming Lin, Chao Wu, Xue Lin, Yanzhi Wang
2024	J	`jnl`	Zero-Shot Neural Architecture Search: Challenges, Solutions, and Opportunities. IEEE Trans. Pattern Anal. Mach. Intell. Guihong Li, Duc Hoang, Kartikeya Bhardwaj, Ming Lin, Zhangyang Wang, Radu Marculescu
2023	J	`jnl`	Agile-Quant: Activation-Guided Quantization for Faster Inference of LLMs on the Edge. CoRR Xuan Shen, Peiyan Dong, Lei Lu, Zhenglun Kong, Zhengang Li, Ming Lin, Chao Wu, Yanzhi Wang
2023	A*	`conf`	DeepMAD: Mathematical Architecture Design for Deep Convolutional Neural Network. CVPR Xuan Shen, Yaohua Wang, Ming Lin, Yilun Huang, Hao Tang, Xiuyu Sun, Yanzhi Wang
2023	J	`jnl`	DeepMAD: Mathematical Architecture Design for Deep Convolutional Neural Network. CoRR Xuan Shen, Yaohua Wang, Ming Lin, Yilun Huang, Hao Tang, Xiuyu Sun, Yanzhi Wang
2023	J	`jnl`	Learning the Relation Between Similarity Loss and Clustering Loss in Self-Supervised Learning. IEEE Trans. Image Process. Jidong Ge, Yuxiang Liu, Jie Gui, Lanting Fang, Ming Lin, James Tin-Yau Kwok, Liguo Huang, Bin Luo
2023	J	`jnl`	Learning the Relation between Similarity Loss and Clustering Loss in Self-Supervised Learning. CoRR Jidong Ge, Yuxiang Liu, Jie Gui, Lanting Fang, Ming Lin, James Tin-Yau Kwok, Liguo Huang, Bin Luo
2023	A*	`conf`	Making Vision Transformers Efficient from A Token Sparsification View. CVPR Shuning Chang, Pichao Wang, Ming Lin, Fan Wang, David Junhao Zhang, Rong Jin, Mike Zheng Shou
2023	J	`jnl`	Making Vision Transformers Efficient from A Token Sparsification View. CoRR Shuning Chang, Pichao Wang, Ming Lin, Fan Wang, David Junhao Zhang, Rong Jin, Mike Zheng Shou
2023	A*	`conf`	Maximizing Spatio-Temporal Entropy of Deep 3D CNNs for Efficient Video Recognition. ICLR Junyan Wang, Zhenhong Sun, Yichen Qian, Dong Gong, Xiuyu Sun, Ming Lin, Maurice Pagnucco, Yang Song
2023	J	`jnl`	Maximizing Spatio-Temporal Entropy of Deep 3D CNNs for Efficient Video Recognition. CoRR Junyan Wang, Zhenhong Sun, Yichen Qian, Dong Gong, Xiuyu Sun, Ming Lin, Maurice Pagnucco, Yang Song
2023	J	`jnl`	Zero-Shot Neural Architecture Search: Challenges, Solutions, and Opportunities. CoRR Guihong Li, Duc Hoang, Kartikeya Bhardwaj, Ming Lin, Zhangyang Wang, Radu Marculescu
2022	A*	`conf`	Ada-NETS: Face Clustering via Adaptive Neighbour Discovery in the Structure Space. ICLR Yaohua Wang, Yaobin Zhang, Fangyi Zhang, Senzhang Wang, Ming Lin, Yuqi Zhang, Xiuyu Sun
2022	J	`jnl`	Ada-NETS: Face Clustering via Adaptive Neighbour Discovery in the Structure Space. CoRR Yaohua Wang, Yaobin Zhang, Fangyi Zhang, Senzhang Wang, Ming Lin, Yuqi Zhang, Xiuyu Sun
2022	A*	`conf`	Entroformer: A Transformer-based Entropy Model for Learned Image Compression. ICLR Yichen Qian, Xiuyu Sun, Ming Lin, Zhiyu Tan, Rong Jin
2022	J	`jnl`	Entroformer: A Transformer-based Entropy Model for Learned Image Compression. CoRR Yichen Qian, Ming Lin, Xiuyu Sun, Zhiyu Tan, Rong Jin
2022	A*	`conf`	Entropy-Driven Mixed-Precision Quantization for Deep Network Design. NeurIPS Zhenhong Sun, Ce Ge, Junyan Wang, Ming Lin, Hesen Chen, Hao Li, Xiuyu Sun
2022	A*	`conf`	GiraffeDet: A Heavy-Neck Paradigm for Object Detection. ICLR Yiqi Jiang, Zhiyu Tan, Junyan Wang, Xiuyu Sun, Ming Lin, Hao Li
2022	J	`jnl`	GiraffeDet: A Heavy-Neck Paradigm for Object Detection. CoRR Yiqi Jiang, Zhiyu Tan, Junyan Wang, Xiuyu Sun, Ming Lin, Hao Li
2022	—	`conf`	KVT: k-NN Attention for Boosting Vision Transformers. ECCV (24) Pichao Wang, Xue Wang, Fan Wang, Ming Lin, Shuning Chang, Hao Li, Rong Jin
2022	A*	`conf`	MAE-DET: Revisiting Maximum Entropy Principle in Zero-Shot NAS for Efficient Object Detection. ICML Zhenhong Sun, Ming Lin, Xiuyu Sun, Zhiyu Tan, Hao Li, Rong Jin
2022	J	`jnl`	Robust Graph Structure Learning over Images via Multiple Statistical Tests. CoRR Yaohua Wang, Fangyi Zhang, Ming Lin, Senzhang Wang, Xiuyu Sun, Rong Jin
2022	A*	`conf`	Robust Graph Structure Learning via Multiple Statistical Tests. NeurIPS Yaohua Wang, Fangyi Zhang, Ming Lin, Senzhang Wang, Xiuyu Sun, Rong Jin
2021	J	`jnl`	Fine-Grained AutoAugmentation for Multi-Label Classification. CoRR Ya Wang, Hesen Chen, Fangyi Zhang, Yaohua Wang, Xiuyu Sun, Ming Lin, Hao Li
2021	J	`jnl`	KVT: k-NN Attention for Boosting Vision Transformers. CoRR Pichao Wang, Xue Wang, Fan Wang, Ming Lin, Shuning Chang, Wen Xie, Hao Li, Rong Jin
2021	A*	`conf`	Learning Accurate Entropy Model with Global Reference for Image Compression. ICLR Yichen Qian, Zhiyu Tan, Xiuyu Sun, Ming Lin, Dongyang Li, Zhenhong Sun, Hao Li, Rong Jin
2021	J	`jnl`	Revisiting Efficient Object Detection Backbones from Zero-Shot Neural Architecture Search. CoRR Zhenhong Sun, Ming Lin, Xiuyu Sun, Zhiyu Tan, Rong Jin
2021	J	`jnl`	Zen-NAS: A Zero-Shot NAS for High-Performance Deep Image Recognition. CoRR Ming Lin, Pichao Wang, Zhenhong Sun, Hesen Chen, Xiuyu Sun, Qi Qian, Hao Li, Rong Jin
2021	A*	`conf`	Zen-NAS: A Zero-Shot NAS for High-Performance Image Recognition. ICCV Ming Lin, Pichao Wang, Zhenhong Sun, Hesen Chen, Xiuyu Sun, Qi Qian, Hao Li, Rong Jin
2020	J	`jnl`	Learning Accurate Entropy Model with Global Reference for Image Compression. CoRR Yichen Qian, Zhiyu Tan, Xiuyu Sun, Ming Lin, Dongyang Li, Zhenhong Sun, Hao Li, Rong Jin
2020	J	`jnl`	Neural Architecture Design for GPU-Efficient Networks. CoRR Ming Lin, Hesen Chen, Xiuyu Sun, Qi Qian, Hao Li, Rong Jin
2020	J	`jnl`	Robust Finite Mixture Regression for Heterogeneous Targets. CoRR Jian Liang, Kun Chen, Ming Lin, Changshui Zhang, Fei Wang
2020	J	`jnl`	WeMix: How to Better Utilize Data Augmentation. CoRR Yi Xu, Asaf Noy, Ming Lin, Qi Qian, Hao Li, Rong Jin
2019	—	`conf`	MuffNet: Multi-Layer Feature Federation for Mobile Deep Learning. ICCV Workshops Hesen Chen, Ming Lin, Xiuyu Sun, Qian Qi, Hao Li, Rong Jin
2019	A*	`conf`	Robust Gaussian Process Regression for Real-Time High Precision GPS Signal Enhancement. KDD Ming Lin, Xiaomin Song, Qi Qian, Hao Li, Liang Sun, Shenghuo Zhu, Rong Jin
2019	J	`jnl`	Robust Gaussian Process Regression for Real-Time High Precision GPS Signal Enhancement. CoRR Ming Lin, Xiaomin Song, Qi Qian, Hao Li, Liang Sun, Shenghuo Zhu, Rong Jin
2019	A*	`conf`	Which Factorization Machine Modeling Is Better: A Theoretical Answer with Optimal Guarantee. AAAI Ming Lin, Shuang Qiu, Jieping Ye, Xiaomin Song, Qi Qian, Liang Sun, Shenghuo Zhu, Rong Jin
2019	J	`jnl`	Which Factorization Machine Modeling is Better: A Theoretical Answer with Optimal Guarantee. CoRR Ming Lin, Shuang Qiu, Jieping Ye, Xiaomin Song, Qi Qian, Liang Sun, Shenghuo Zhu, Rong Jin
2018	J	`jnl`	On the Generalization Ability of Online Gradient Descent Algorithm Under the Quadratic Growth Condition. IEEE Trans. Neural Networks Learn. Syst. Daqing Chang, Ming Lin, Changshui Zhang
2018	J	`jnl`	Robust finite mixture regression for heterogeneous targets. Data Min. Knowl. Discov. Jian Liang, Kun Chen, Ming Lin, Changshui Zhang, Fei Wang
2017	J	`jnl`	Feature Interaction Augmented Sparse Learning for Fast Kinect Motion Detection. IEEE Trans. Image Process. Xiaojun Chang, Zhigang Ma, Ming Lin, Yi Yang, Alexander G. Hauptmann
2017	—	`conf`	Self-paced Convolutional Neural Network for Computer Aided Detection in Medical Imaging Analysis. MLMI@MICCAI Xiang Li, Aoxiao Zhong, Ming Lin, Ning Guo, Mu Sun, Arkadiusz Sitek, Jieping Ye, James Thrall, Quanzheng Li
2017	J	`jnl`	Self-paced Convolutional Neural Network for Computer Aided Detection in Medical Imaging Analysis. CoRR Xiang Li, Aoxiao Zhong, Ming Lin, Ning Guo, Mu Sun, Arkadiusz Sitek, Jieping Ye, James Thrall, Quanzheng Li
2016	A*	`conf`	Concepts Not Alone: Exploring Pairwise Relationships for Zero-Shot Video Activity Recognition. AAAI Chuang Gan, Ming Lin, Yi Yang, Gerard de Melo, Alexander G. Hauptmann
2016	J	`jnl`	Online kernel learning with nearly constant support vectors. Neurocomputing Ming Lin, Lijun Zhang, Rong Jin, Shifeng Weng, Changshui Zhang
2016	J	`jnl`	Strategies for Searching Video Content with Text Queries or Video Examples. CoRR Shoou-I Yu, Yi Yang, Zhongwen Xu, Shicheng Xu, Deyu Meng, Zexi Mao, Zhigang Ma, Ming Lin, Xuanchong Li, Huan Li, Zhen-Zhong Lan, Lu Jiang, Alexander G. Hauptmann, Chuang Gan, Xingzhong Du, Xiaojun Chang
2016	—	`conf`	The Best of BothWorlds: Combining Data-Independent and Data-Driven Approaches for Action Recognition. CVPR Workshops Zhen-Zhong Lan, Shoou-I Yu, Dezhong Yao, Ming Lin, Bhiksha Raj, Alexander G. Hauptmann
2015	A*	`conf`	Beyond Gaussian Pyramid: Multi-skip Feature Stacking for action recognition. CVPR Zhen-Zhong Lan, Ming Lin, Xuanchong Li, Alexander G. Hauptmann, Bhiksha Raj
2015	—	`conf`	CMU Informedia@TRECVID 2015: MED/SIN/LNK/SED. TRECVID Shoou-I Yu, Lu Jiang, Zhongwen Xu, Zhenzhong Lan, Shicheng Xu, Xiaojun Chang, Xuanchong Li, Zexi Mao, Chuang Gan, Yajie Miao, Xingzhong Du, Yang Cai, Lara J. Martin, Nikolas Wolfe, Anurag Kumar, 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 M. Stern, Alexander G. Hauptmann
2015	J	`jnl`	Damping proximal coordinate descent algorithm for non-convex regularization. Neurocomputing Zheng Pan, Ming Lin, Guangdong Hou, Changshui Zhang
2015	A*	`conf`	Density Corrected Sparse Recovery when R.I.P. Condition Is Broken. IJCAI Ming Lin, Zhen-Zhong Lan, Alexander G. Hauptmann
2015	J	`jnl`	Dependent Online Kernel Learning With Constant Number of Random Fourier Features. IEEE Trans. Neural Networks Learn. Syst. Zhen Hu, Ming Lin, Changshui Zhang
2015	A*	`conf`	Exploring Semantic Inter-Class Relationships (SIR) for Zero-Shot Action Recognition. AAAI Chuang Gan, Ming Lin, Yi Yang, Yueting Zhuang, Alexander G. Hauptmann
2015	J	`jnl`	Handcrafted Local Features are Convolutional Neural Networks. CoRR Zhen-Zhong Lan, Shoou-I Yu, Ming Lin, Bhiksha Raj, Alexander G. Hauptmann
2015	J	`jnl`	Large-scale eigenvector approximation via Hilbert Space Embedding Nyström. Pattern Recognit. Ming Lin, Fei Wang, Changshui Zhang
2015	J	`jnl`	Long-short Term Motion Feature for Action Classification and Retrieval. CoRR Zhen-Zhong Lan, Xuanchong Li, Ming Lin, Alexander G. Hauptmann
2015	J	`jnl`	The Best of Both Worlds: Combining Data-independent and Data-driven Approaches for Action Recognition. CoRR Zhen-Zhong Lan, Dezhong Yao, Ming Lin, Shoou-I Yu, Alexander G. Hauptmann
2014	J	`jnl`	Beyond Gaussian Pyramid: Multi-skip Feature Stacking for Action Recognition. CoRR Zhen-Zhong Lan, Ming Lin, Xuanchong Li, Alexander G. Hauptmann, Bhiksha Raj
2014	A	`conf`	Efficient Sparse Recovery via Adaptive Non-Convex Regularizers with Oracle Property. UAI Ming Lin, Rong Jin, Changshui Zhang
2014	—	`conf`	Informedia @ TRECVID 2014. TRECVID Shoou-I Yu, Lu Jiang, Zhongwen Xu, Zhenzhong Lan, Shicheng Xu, Xiaojun Chang, Xuanchong Li, Zexi Mao, Chuang Gan, Yajie Miao, Xingzhong Du, Yang Cai, Lara J. Martin, Nikolas Wolfe, Anurag Kumar, 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 M. Stern, Alexander G. Hauptmann, Anil Armagan, Yicheng Zhao
2013	J	`jnl`	On the Sample Complexity of Random Fourier Features for Online Learning: How Many Random Fourier Features Do We Need? ACM Trans. Knowl. Discov. Data Ming Lin, Shifeng Weng, Changshui Zhang
2013	—	`conf`	Online Kernel Learning with a Near Optimal Sparsity Bound. ICML (3) Lijun Zhang, Jinfeng Yi, Rong Jin, Ming Lin, Xiaofei He
2012	J	`jnl`	A general framework for transfer sparse subspace learning. Neural Comput. Appl. Shizhun Yang, Ming Lin, Chenping Hou, Changshui Zhang, Yi Wu