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2020 – today
- 2022
[c14]Xin Chen, Qingtao Tang, Ke Hu, Yue Xu, Shihang Qiu, Jia Cheng, Jun Lei:
Hybrid CNN Based Attention with Category Prior for User Image Behavior Modeling. SIGIR 2022: 2336-2340- [i6]Xin Chen, Qingtao Tang, Ke Hu, Yue Xu, Shihang Qiu, Jia Cheng, Jun Lei:
Hybrid CNN Based Attention with Category Prior for User Image Behavior Modeling. CoRR abs/2205.02711 (2022) - 2021
- [c13]Yiming Li
, Yang Zhang, Qingtao Tang, Weipéng Huáng, Yong Jiang, Shu-Tao Xia:
t-k-means: A ROBUST AND STABLE k-means VARIANT. ICASSP 2021: 3120-3124 - [c12]Jianqiang Huang, Ke Hu, Qingtao Tang, Mingjian Chen, Yi Qi, Jia Cheng, Jun Lei:
Deep Position-wise Interaction Network for CTR Prediction. SIGIR 2021: 1885-1889 - [i5]Jianqiang Huang, Ke Hu, Qingtao Tang, Mingjian Chen, Yi Qi, Jia Cheng, Jun Lei:
Deep Position-wise Interaction Network for CTR Prediction. CoRR abs/2106.05482 (2021) - 2020
- [i4]Xingchun Xiang, Qingtao Tang, Huaixuan Zhang, Tao Dai, Jiawei Li, Shu-Tao Xia:
JSRT: James-Stein Regression Tree. CoRR abs/2010.09022 (2020)
2010 – 2019
- 2019
- [i3]Yiming Li, Jiawang Bai, Qingtao Tang, Yong Jiang, Chun Li, Shutao Xia:
Multinomial Random Forests: Fill the Gap between Theoretical Consistency and Empirical Soundness. CoRR abs/1903.04003 (2019) - [i2]Yang Zhang, Qingtao Tang, Yiming Li, Weipéng Huáng, Shutao Xia:
t-k-means: A k-means Variant with Robustness and Stability. CoRR abs/1907.07442 (2019) - 2018
- [j2]Yisen Wang, Shu-Tao Xia, Qingtao Tang, Jia Wu, Xingquan Zhu:
A Novel Consistent Random Forest Framework: Bernoulli Random Forests. IEEE Trans. Neural Networks Learn. Syst. 29(8): 3510-3523 (2018) - [c11]Li Niu, Qingtao Tang, Ashok Veeraraghavan, Ashutosh Sabharwal:
Learning From Noisy Web Data With Category-Level Supervision. CVPR 2018: 7689-7698 - [c10]Zhiya Xu, Tao Dai, Li Niu, Jiawei Li, Qingtao Tang, Shu-Tao Xia:
Sure-Based Dual Domain Image Denoising. ICASSP 2018: 1418-1422 - [c9]Yang Zhang, Qingtao Tang, Li Niu, Tao Dai, Xi Xiao, Shu-Tao Xia:
Self -Paced Mixture of T Distribution Model. ICASSP 2018: 2796-2800 - [c8]Jiawei Li, Tao Dai, Qingtao Tang, Yeli Xing, Shu-Tao Xia:
Cyclic Annealing Training Convolutional Neural Networks for Image Classification with Noisy Labels. ICIP 2018: 21-25 - [c7]Yeli Xing, Jiawei Li, Tao Dai, Qingtao Tang, Li Niu, Shu-Tao Xia:
Portrait-Aware Artistic Style Transfer. ICIP 2018: 2117-2121 - [i1]Li Niu, Qingtao Tang, Ashok Veeraraghavan, Ashutosh Sabharwal:
Learning from Noisy Web Data with Category-level Supervision. CoRR abs/1803.03857 (2018) - 2017
- [j1]Tao Dai, Zhiya Xu, Haoyi Liang, Ke Gu, Qingtao Tang, Yisen Wang, Weizhi Lu, Shu-Tao Xia:
A generic denoising framework via guided principal component analysis. J. Vis. Commun. Image Represent. 48: 340-352 (2017) - [c6]Tao Dai, Ke Gu, Zhiya Xu, Qingtao Tang, Haoyi Liang, Yong-bing Zhang, Shu-Tao Xia:
Blind quality assessment of multiply-distorted images based on structural degradation. ICIP 2017: 171-175 - [c5]Tao Dai, Ke Gu, Qingtao Tang, Kwok-Wai Hung, Yong-bing Zhang, Weizhi Lu, Shu-Tao Xia:
Foveated nonlocal dual denoising. ICIP 2017: 1881-1885 - [c4]Qingtao Tang, Li Niu, Yisen Wang, Tao Dai, Wangpeng An, Jianfei Cai, Shu-Tao Xia:
Student-t Process Regression with Student-t Likelihood. IJCAI 2017: 2822-2828 - [c3]Qingtao Tang, Tao Dai, Li Niu, Yisen Wang, Shu-Tao Xia, Jianfei Cai:
Robust Survey Aggregation with Student-t Distribution and Sparse Representation. IJCAI 2017: 2829-2835 - 2016
- [c2]Qingtao Tang, Yisen Wang, Shu-Tao Xia:
Student-t Process Regression with Dependent Student-t Noise. ECAI 2016: 82-89 - [c1]Yisen Wang, Qingtao Tang, Shu-Tao Xia, Jia Wu, Xingquan Zhu:
Bernoulli Random Forests: Closing the Gap between Theoretical Consistency and Empirical Soundness. IJCAI 2016: 2167-2173
Coauthor Index
aka: Shu-Tao Xia
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