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Year
Latent cross: Making use of context in recurrent recommender systems
A Beutel, P Covington, S Jain, C Xu, J Li, V Gatto, EH Chi
Proceedings of the Eleventh ACM International Conference on Web Search and …, 2018
3002018
Towards neural mixture recommender for long range dependent user sequences
J Tang, F Belletti, S Jain, M Chen, A Beutel, C Xu, E H. Chi
The World Wide Web Conference, 1782-1793, 2019
722019
User response models to improve a reinforce recommender system
M Chen, B Chang, C Xu, EH Chi
Proceedings of the 14th ACM International Conference on Web Search and Data …, 2021
152021
Learning receptive fields for pooling from tensors of feature response
C Xu, N Vasconcelos
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2014
62014
Values of user exploration in recommender systems
M Chen, Y Wang, C Xu, Y Le, M Sharma, L Richardson, SL Wu, E Chi
Proceedings of the 15th ACM Conference on Recommender Systems, 85-95, 2021
42021
Off-Policy Actor-critic for Recommender Systems
M Chen, C Xu, V Gatto, D Jain, A Kumar, E Chi
Proceedings of the 16th ACM Conference on Recommender Systems, 338-349, 2022
32022
Surrogate for Long-Term User Experience in Recommender Systems
Y Wang, M Sharma, C Xu, S Badam, Q Sun, L Richardson, L Chung, ...
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022
22022
Latent User Intent Modeling for Sequential Recommenders
B Chang, A Karatzoglou, Y Wang, C Xu, EH Chi, M Chen
arXiv preprint arXiv:2211.09832, 2022
2022
Reward Shaping for User Satisfaction in a REINFORCE Recommender
K Christakopoulou, C Xu, S Zhang, S Badam, T Potter, D Li, H Wan, X Yi, ...
arXiv preprint arXiv:2209.15166, 2022
2022
Recency Dropout for Recurrent Recommender Systems
B Chang, C Xu, M Lę, J Feng, Y Le, S Badam, E Chi, M Chen
arXiv preprint arXiv:2201.11016, 2022
2022
Visual sentiment prediction with deep convolutional neural networks
X Can, C Suleyman, L Kuang-Chih, L Li-Jia
Retrieved from: Arxiv Preprint Arxiv 1411, 2014
2014
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