A novel consistent random forest framework: Bernoulli random forests Y Wang, ST Xia, Q Tang, J Wu, X Zhu IEEE transactions on neural networks and learning systems 29 (8), 3510-3523, 2017 | 104 | 2017 |
Learning from noisy web data with category-level supervision L Niu, Q Tang, A Veeraraghavan, A Sabharwal Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018 | 34 | 2018 |
Deep position-wise interaction network for ctr prediction J Huang, K Hu, Q Tang, M Chen, Y Qi, J Cheng, J Lei Proceedings of the 44th International ACM SIGIR Conference on Research and …, 2021 | 24 | 2021 |
Student-t process regression with student-t likelihood Q Tang, L Niu, Y Wang, T Dai, W An, J Cai, ST Xia International Joint Conference on Artificial Intelligence 2017, 2822-2828, 2017 | 23 | 2017 |
tk-means: A robust and stable k-means variant Y Li, Y Zhang, Q Tang, W Huang, Y Jiang, ST Xia ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021 | 18 | 2021 |
Bernoulli random forests: Closing the gap between theoretical consistency and empirical soundness W Yisen, T Qingtao, ST Xia, J Wu, X Zhu IJCAI International Joint Conference on Artificial Intelligence, 2016 | 15 | 2016 |
Student-t Process Regression with Dependent Student-t Noise Q Tang, Y Wang, ST Xia ECAI 2016: 22nd European Conference on Artificial Intelligence, 29 August-2 …, 2016 | 13 | 2016 |
Cyclic annealing training convolutional neural networks for image classification with noisy labels J Li, T Dai, Q Tang, Y Xing, ST Xia 2018 25th IEEE International Conference on Image Processing (ICIP), 21-25, 2018 | 11 | 2018 |
A generic denoising framework via guided principal component analysis T Dai, Z Xu, H Liang, K Gu, Q Tang, Y Wang, W Lu, ST Xia Journal of Visual Communication and Image Representation 48, 340-352, 2017 | 11 | 2017 |
Portrait-aware artistic style transfer Y Xing, J Li, T Dai, Q Tang, L Niu, ST Xia 2018 25th IEEE International Conference on Image Processing (ICIP), 2117-2121, 2018 | 7 | 2018 |
Sure-based dual domain image denoising Z Xu, T Dai, L Niu, J Li, Q Tang, ST Xia 2018 IEEE International Conference on Acoustics, Speech and Signal …, 2018 | 5 | 2018 |
Self-paced mixture of t distribution model Y Zhang, Q Tang, L Niu, T Dai, X Xiao, ST Xia 2018 IEEE International Conference on Acoustics, Speech and Signal …, 2018 | 5 | 2018 |
Foveated nonlocal dual denoising T Dai, K Gu, Q Tang, KW Hung, Y Zhang, W Lu, ST Xia 2017 IEEE International Conference on Image Processing (ICIP), 1881-1885, 2017 | 5 | 2017 |
Hybrid CNN Based Attention with Category Prior for User Image Behavior Modeling X Chen, Q Tang, K Hu, Y Xu, S Qiu, J Cheng, J Lei Proceedings of the 45th International ACM SIGIR Conference on Research and …, 2022 | 4 | 2022 |
Robust survey aggregation with student-t distribution and sparse representation Q Tang, T Dai, L Niu, Y Wang, ST Xia, J Cai International Joint Conference on Artificial Intelligence 2017, 2829-2835, 2017 | 4 | 2017 |
Blind quality assessment of multiply-distorted images based on structural degradation T Dai, K Gu, Z Xu, Q Tang, H Liang, Y Zhang, ST Xia 2017 IEEE International Conference on Image Processing (ICIP), 171-175, 2017 | 2 | 2017 |
JSRT: James-Stein Regression Tree X Xiang, Q Tang, H Zhang, T Dai, J Li, ST Xia arXiv preprint arXiv:2010.09022, 2020 | 1 | 2020 |
Multinomial random forests: fill the gap between theoretical consistency and empirical soundness JW Bai, YM Li, JW Li, QT Tang, Y Jiang, C Li, ST Xia Pattern Recognition 1903, 2019 | 1 | 2019 |
tk-means: A k-means Variant with Robustness and Stability Y Zhang, Q Tang, Y Li, W Huang, S Xia arXiv preprint arXiv:1907.07442, 2019 | | 2019 |
tk-means: A ROBUST AND STABLE k-means VARIANT Yiming Li1, Yang Zhang1, Qingtao Tang1, Weipeng Huang2, Yong Jiang1, 3, Shu-Tao Xia1, 3 1Tsinghua Shenzhen International Graduate … Y Li, Y Zhang, Q Tang, W Huang, Y Jiang, ST Xia | | |