Xing Zhao
Xing Zhao
Verified email at tamu.edu
Title
Cited by
Cited by
Year
Swell-noise attenuation: A deep learning approach
X Zhao, P Lu, Y Zhang, J Chen, X Li
The Leading Edge 38 (12), 934-942, 2019
162019
Learning to hash with graph neural networks for recommender systems
Q Tan, N Liu, X Zhao, H Yang, J Zhou, X Hu
Proceedings of The Web Conference 2020, 1988-1998, 2020
142020
Popularity-Opportunity Bias in Collaborative Filtering
Z Zhu, Y He, X Zhao, Y Zhang, J Wang, J Caverlee
Proceedings of the 14th ACM International Conference on Web Search and Data …, 2021
92021
Improving the estimation of tail ratings in recommender system with multi-latent representations
X Zhao, Z Zhu, Y Zhang, J Caverlee
Proceedings of the 13th International Conference on Web Search and Data …, 2020
62020
Trailmix: An ensemble recommender system for playlist curation and continuation
X Zhao, Q Song, J Caverlee, X Hu
Proceedings of the ACM Recommender Systems Challenge 2018, 1-6, 2018
52018
Generative Inpainting Network Applications on Seismic Image Compression and Non-Uniform Sampling
XR Li, N Mitsakos, P Lu, Y Xiao, X Zhao
32019
Vitriol on social media: Curation and investigation
X Zhao, J Caverlee
International Conference on Social Informatics, 487-504, 2018
22018
Popularity Bias in Dynamic Recommendation
Z Zhu, Y He, X Zhao, J Caverlee
12021
Addressing the Target Customer Distortion Problem in Recommender Systems
X Zhao, Z Zhu, M Alfifi, J Caverlee
Proceedings of The Web Conference 2020, 2969-2975, 2020
12020
Seismic compressive sensing by generative inpainting network: Toward an optimized acquisition survey
XR Li, N Mitsakos, P Lu, Y Xiao, X Zhao
The Leading Edge 38 (12), 923-933, 2019
12019
Rabbit Holes and Taste Distortion: Distribution-Aware Recommendation with Evolving Interests
X Zhao, Z Zhu, J Caverlee
Proceedings of the Web Conference 2021, 888-899, 2021
2021
Attenuating Random Noise in Seismic Data by a Deep Learning Approach
X Zhao, P Lu, Y Zhang, J Chen, X Li
arXiv preprint arXiv:1910.12800, 2019
2019
SEISMIC COMPRESSIVE SENSING BY GENERATIVE INPAINTING NETWORK AND RECOMMENDATION OF EFFICIENT SEISMIC ACQUIZAITON TOWARD NON-UNIFORM SURVEY
XR Li, N Mitsakos, P Lu, Y Xiao, X Zhao
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Articles 1–13