Kun Gai
Kun Gai
Senior Director & Researcher, Alibaba Group
Verified email at taobao.com
Title
Cited by
Cited by
Year
Deep interest network for click-through rate prediction
G Zhou, X Zhu, C Song, Y Fan, H Zhu, X Ma, Y Yan, J Jin, H Li, K Gai
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge …, 2018
3882018
Deep interest evolution network for click-through rate prediction
G Zhou, N Mou, Y Fan, Q Pi, W Bian, C Zhou, X Zhu, K Gai
Proceedings of the AAAI conference on artificial intelligence 33 (01), 5941-5948, 2019
1602019
Blind separation of superimposed moving images using image statistics
K Gai, Z Shi, C Zhang
IEEE transactions on pattern analysis and machine intelligence 34 (1), 19-32, 2011
1042011
Learning tree-based deep model for recommender systems
H Zhu, X Li, P Zhang, G Li, J He, H Li, K Gai
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge …, 2018
772018
Real-time bidding with multi-agent reinforcement learning in display advertising
J Jin, C Song, H Li, K Gai, J Wang, W Zhang
Proceedings of the 27th ACM International Conference on Information and …, 2018
672018
Learning kernels with radiuses of minimum enclosing balls
K Gai, G Chen, C Zhang
Advances in neural information processing systems 23, 649-657, 2010
552010
Optimized cost per click in taobao display advertising
H Zhu, J Jin, C Tan, F Pan, Y Zeng, H Li, K Gai
Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge …, 2017
442017
Blindly separating mixtures of multiple layers with spatial shifts
K Gai, Z Shi, C Zhang
2008 IEEE Conference on Computer Vision and Pattern Recognition, 1-8, 2008
442008
Entire space multi-task model: An effective approach for estimating post-click conversion rate
X Ma, L Zhao, G Huang, Z Wang, Z Hu, X Zhu, K Gai
The 41st International ACM SIGIR Conference on Research & Development in …, 2018
402018
Rocket launching: A universal and efficient framework for training well-performing light net
G Zhou, Y Fan, R Cui, W Bian, X Zhu, K Gai
Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018
362018
Budget constrained bidding by model-free reinforcement learning in display advertising
D Wu, X Chen, X Yang, H Wang, Q Tan, X Zhang, J Xu, K Gai
Proceedings of the 27th ACM International Conference on Information and …, 2018
332018
Practice on long sequential user behavior modeling for click-through rate prediction
Q Pi, W Bian, G Zhou, X Zhu, K Gai
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge …, 2019
312019
Semantic human matting
Q Chen, T Ge, Y Xu, Z Zhang, X Yang, K Gai
Proceedings of the 26th ACM international conference on Multimedia, 618-626, 2018
312018
Learning piece-wise linear models from large scale data for ad click prediction
K Gai, X Zhu, H Li, K Liu, Z Wang
arXiv preprint arXiv:1704.05194, 2017
292017
Blind separation of superimposed images with unknown motions
K Gai, Z Shi, C Zhang
2009 IEEE Conference on Computer Vision and Pattern Recognition, 1881-1888, 2009
272009
Efficient euclidean projections via piecewise root finding and its application in gradient projection
P Gong, K Gai, C Zhang
Neurocomputing 74 (17), 2754-2766, 2011
262011
Lifelong sequential modeling with personalized memorization for user response prediction
K Ren, J Qin, Y Fang, W Zhang, L Zheng, W Bian, G Zhou, J Xu, Y Yu, ...
Proceedings of the 42nd International ACM SIGIR Conference on Research and …, 2019
222019
Image matters: Visually modeling user behaviors using advanced model server
T Ge, L Zhao, G Zhou, K Chen, S Liu, H Yi, Z Hu, B Liu, P Sun, H Liu, P Yi, ...
Proceedings of the 27th ACM International Conference on Information and …, 2018
162018
Joint optimization of tree-based index and deep model for recommender systems
H Zhu, D Chang, Z Xu, P Zhang, X Li, J He, H Li, J Xu, K Gai
arXiv preprint arXiv:1902.07565, 2019
122019
Learning discriminative piecewise linear models with boundary points
K Gai, C Zhang
Proceedings of the AAAI Conference on Artificial Intelligence 24 (1), 2010
112010
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Articles 1–20