Ming Lin
Ming Lin
Alibaba Group
Verified email at - Homepage
Cited by
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Beyond gaussian pyramid: Multi-skip feature stacking for action recognition
Z Lan, M Lin, X Li, AG Hauptmann, B Raj
Proceedings of the IEEE conference on computer vision and pattern …, 2015
Feature interaction augmented sparse learning for fast kinect motion detection
X Chang, Z Ma, M Lin, Y Yang, AG Hauptmann
IEEE transactions on image processing 26 (8), 3911-3920, 2017
Exploring semantic inter-class relationships (sir) for zero-shot action recognition
C Gan, M Lin, Y Yang, Y Zhuang, AG Hauptmann
Proceedings of the AAAI Conference on Artificial Intelligence 29 (1), 2015
Concepts not alone: Exploring pairwise relationships for zero-shot video activity recognition
C Gan, M Lin, Y Yang, G De Melo, AG Hauptmann
Thirtieth AAAI conference on artificial intelligence, 2016
Informedia@ trecvid 2014 med and mer
SI Yu, L Jiang, Z Mao, X Chang, X Du, C Gan, Z Lan, Z Xu, X Li, Y Cai, ...
NIST TRECVID Video Retrieval Evaluation Workshop 24, 2014
Online kernel learning with a near optimal sparsity bound
L Zhang, J Yi, R Jin, M Lin, X He
International Conference on Machine Learning, 621-629, 2013
A non-convex one-pass framework for generalized factorization machine and rank-one matrix sensing
M Lin, J Ye
Advances in Neural Information Processing Systems 29, 2016
Dependent online kernel learning with constant number of random fourier features
Z Hu, M Lin, C Zhang
IEEE transactions on neural networks and learning systems 26 (10), 2464-2476, 2015
A general framework for transfer sparse subspace learning
S Yang, M Lin, C Hou, C Zhang, Y Wu
Neural Computing and Applications 21 (7), 1801-1817, 2012
Big data analytical approaches to the NACC dataset: aiding preclinical trial enrichment
M Lin, P Gong, T Yang, J Ye, RL Albin, HH Dodge
Alzheimer disease and associated disorders 32 (1), 18, 2018
Knapsack pruning with inner distillation
Y Aflalo, A Noy, M Lin, I Friedman, L Zelnik
arXiv preprint arXiv:2002.08258, 2020
On the sample complexity of random fourier features for online learning: How many random fourier features do we need?
M Lin, S Weng, C Zhang
ACM Transactions on Knowledge Discovery from Data (TKDD) 8 (3), 1-19, 2014
Margin based PU learning
T Gong, G Wang, J Ye, Z Xu, M Lin
Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018
Handcrafted local features are convolutional neural networks
Z Lan, SI Yu, M Lin, B Raj, AG Hauptmann
arXiv preprint arXiv:1511.05045, 2015
The best of both worlds: Combining data-independent and data-driven approaches for action recognition
Z Lan, SI Yu, D Yao, M Lin, B Raj, A Hauptmann
Proceedings of the IEEE conference on computer vision and pattern …, 2016
Self-paced convolutional neural network for computer aided detection in medical imaging analysis
X Li, A Zhong, M Lin, N Guo, M Sun, A Sitek, J Ye, J Thrall, Q Li
International Workshop on Machine Learning in Medical Imaging, 212-219, 2017
Online kernel learning with nearly constant support vectors
M Lin, L Zhang, R Jin, S Weng, C Zhang
Neurocomputing 179, 26-36, 2016
Kvt: k-nn attention for boosting vision transformers
P Wang, X Wang, F Wang, M Lin, S Chang, W Xie, H Li, R Jin
arXiv preprint arXiv:2106.00515, 2021
Learning accurate entropy model with global reference for image compression
Y Qian, Z Tan, X Sun, M Lin, D Li, Z Sun, H Li, R Jin
arXiv preprint arXiv:2010.08321, 2020
Robust gaussian process regression for real-time high precision GPS signal enhancement
M Lin, X Song, Q Qian, H Li, L Sun, S Zhu, R Jin
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge …, 2019
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