Mingming Gong

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Tongliang LiuDirector, Sydney AI Centre, University of Sydney & Mohamed bin Zayed University of AIVerified email at sydney.edu.au
Dacheng TaoNanyang Technological UniversityVerified email at ntu.edu.sg
Kun ZhangCarnegie Mellon University & Mohamed bin Zayed University of Artificial Intelligence (MBZUAI)Verified email at cmu.edu
Kayhan BatmanghelichAssistant Professor, Boston UniversityVerified email at bu.edu
Bo HanHKBU / RIKENVerified email at comp.hkbu.edu.hk
Biwei HuangUCSDVerified email at andrew.cmu.edu
Gang NiuSenior Research Scientist (tenured), RIKEN Center for Advanced Intelligence ProjectVerified email at riken.jp
Chaohui WangLaboratoire d'Informatique Gaspard-Monge | Université Gustave Eiffel - CNRS - Ecole de PontsVerified email at u-pem.fr
Xiaobo XiaPostdoc, National University of SingaporeVerified email at nus.edu.sg
Clark GlymourCarnegie Mellon UniversityVerified email at andrew.cmu.edu
Yu YaoLecturer in the University of SydneyVerified email at sydney.edu.au
Masashi SugiyamaDirector, RIKEN Center for Advanced Intelligence Project / Professor, The University of TokyoVerified email at k.u-tokyo.ac.jp
Bernhard SchölkopfDirector, Max Planck Institute for Intelligent Systems & ELLIS Institute Tübingen; Professor at ETHVerified email at tuebingen.mpg.de
Zhaoqing Wang (Derrick)Ph.D., Sydney AI Centre, University of SydneyVerified email at uni.sydney.edu.au
Shanshan ZhaoAlibabaVerified email at uni.sydney.edu.au
Nannan WangProfessor, Xidian UniversityVerified email at xidian.edu.cn
bo duSchool of Computer Science, Wuhan UniversityVerified email at whu.edu.cn
Yanwu XuBoston UniversityVerified email at bu.edu
Professor Javen Qinfeng ShiDirector for Causal AI Group, University of AdelaideVerified email at adelaide.edu.au
Shaoan XieCarnegie Mellon UniversityVerified email at cmu.edu

Mingming Gong

University of Melbourne & Mohamed bin Zayed University of Artificial Intelligence

Verified email at unimelb.edu.au - Homepage

Causal Inference Machine Learning Computer Vision


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Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge S Bakas, M Reyes, A Jakab, S Bauer, M Rempfler, A Crimi, RT Shinohara, ... arXiv preprint arXiv:1811.02629, 2018	2322	2018
Deep Ordinal Regression Network for Monocular Depth Estimation H Fu, M Gong, C Wang, K Batmanghelich, D Tao Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018	2159	2018
Deep Domain Generalization via Conditional Invariant Adversarial Networks Y Li, X Tian, M Gong, Y Liu, T Liu, K Zhang, D Tao Proceedings of the European Conference on Computer Vision (ECCV), 624-639, 2018	853	2018
Domain Adaptation with Conditional Transferable Components M Gong, K Zhang, T Liu, D Tao, C Glymour, B Schölkopf Proceedings of The 33rd International Conference on Machine Learning, 2839-2848, 2016	425	2016
Cris: Clip-driven referring image segmentation Z Wang, Y Lu, Q Li, X Tao, Y Guo, M Gong, T Liu Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022	415	2022
Part-dependent label noise: Towards instance-dependent label noise X Xia, T Liu, B Han, N Wang, M Gong, H Liu, G Niu, D Tao, M Sugiyama Advances in Neural Information Processing Systems 33, 7597-7610, 2020	345	2020
Sub-center arcface: Boosting face recognition by large-scale noisy web faces J Deng, J Guo, T Liu, M Gong, S Zafeiriou European Conference on Computer Vision, 741-757, 2020	289	2020
Dual t: Reducing estimation error for transition matrix in label-noise learning Y Yao, T Liu, B Han, M Gong, J Deng, G Niu, M Sugiyama Advances in Neural Information Processing Systems 33, 2020	277	2020
Domain generalization via entropy regularization S Zhao, M Gong, T Liu, H Fu, D Tao Advances in Neural Information Processing Systems 33, 16096-16107, 2020	275	2020
Geometry-consistent generative adversarial networks for one-sided unsupervised domain mapping H Fu, M Gong, C Wang, K Batmanghelich, K Zhang, D Tao Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019	274	2019
Domain generalization via conditional invariant representations Y Li, M Gong, X Tian, T Liu, D Tao Thirty-Second AAAI Conference on Artificial Intelligence, 2018	255	2018
Learning with biased complementary labels X Yu, T Liu, M Gong, D Tao Proceedings of the European Conference on Computer Vision (ECCV), 68-83, 2018	236	2018
3d-future: 3d furniture shape with texture H Fu, R Jia, L Gao, M Gong, B Zhao, S Maybank, D Tao International Journal of Computer Vision, 1-25, 2021	232	2021
Geometry-aware symmetric domain adaptation for monocular depth estimation S Zhao, H Fu, M Gong, D Tao Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019	226	2019
A coarse-fine network for keypoint localization S Huang, M Gong, D Tao Proceedings of the IEEE International Conference on Computer Vision, 3028-3037, 2017	226	2017
Multi-source domain adaptation: A causal view K Zhang, M Gong, B Schölkopf Twenty-ninth AAAI conference on artificial intelligence, 2015	225	2015
Adaptive context-aware multi-modal network for depth completion S Zhao, M Gong, H Fu, D Tao IEEE Transactions on Image Processing 30, 5264-5276, 2021	179	2021
Sample Selection with Uncertainty of Losses for Learning with Noisy Labels X Xia, T Liu, B Han, M Gong, J Yu, G Niu, M Sugiyama arXiv preprint arXiv:2106.00445, 2021	151	2021
Machine learning (ML)–Centric resource management in cloud computing: A review and future directions T Khan, W Tian, G Zhou, S Ilager, M Gong, R Buyya Journal of Network and Computer Applications, 103405, 2022	138	2022
Correcting the Triplet Selection Bias for Triplet Loss B Yu, T Liu, M Gong, C Ding, D Tao Proceedings of the European Conference on Computer Vision (ECCV), 71-87, 2018	126	2018

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