Xingjun (Daniel) is currently a Postdoctoral Research Fellow and previously a PHD student at School of Computing and Information Systems, University of Melbourne. I am a passionate researcher with broad interests in machine learning and deep learning theory/applications: adversarial deep learning, noisy label learning and generative adversarial networks (GANs).
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Development and Validation of a Virtual Reality Tutor to Teach Clinically Oriented Surgica..
Displaying the 15 most recent scholarly works by Daniel Ma.
Symmetric cross entropy for robust learning with noisy labels
Y Wang, X Ma, Z Chen, Y Luo, J Yi, J Bailey
Conference Proceedings | 2020 | 2019 IEEE/CVF International Conference on Computer Vision (ICCV)
Training accurate deep neural networks (DNNs) in the presence of noisy labels is an important and challenging task. Though a numbe..
Black-box adversarial attacks on video recognition models
L Jiang, X Ma, S Chen, J Bailey, YG Jiang
Conference Proceedings | 2019 | Proceedings of the 27th ACM International Conference on Multimedia
Deep neural networks (DNNs) are known for their vulnerability to adversarial examples. These are examples that have undergone smal..
On the convergence and robustness of adversarial training
Y Wang, X Ma, J Bailey, J Yi, B Zhou, Q Gu
Conference Proceedings | 2019 | 36th International Conference on Machine Learning, ICML 2019
Improving the robustness of deep neural networks (DNNs) to adversarial examples is an important yet challenging problem for secure..
Generative image inpainting with submanifold alignment
A Li, J Qi, R Zhang, X Ma, K Ramamohanarao
Conference Proceedings | 2019 | Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence
Image inpainting aims at restoring missing regions of corrupted images, which has many applications such as image restoration and ..
Development and Validation of a Virtual Reality Tutor to Teach Clinically Oriented Surgical Anatomy of the Ear
S Wijewickrema, B Copson, X Ma, R Briggs, J Bailey, G Kennedy, S Oleary
Conference Proceedings | 2018 | 2018 IEEE 31st International Symposium on Computer-Based Medical Systems (CBMS)
© 2018 IEEE. Virtual reality (VR) is being increasingly used in medical education. However, investigations into its effectiveness ..
Dimensionality-Driven Learning with Noisy Labels
X Ma, Yisen Wang, Michael E Houle, Shuo Zhou, Sarah M Erfani, Shu-tao Xia, Sudanthi Wijewickrema, James Bailey
Conference Proceedings | 2018 | 35th International Conference on Machine Learning, ICML 2018
Datasets with significant proportions of noisy (incorrect) class labels present challenges for training accurate Deep Neural Netwo..
Iterative Learning with Open-set Noisy Labels
Yisen Wang, Weiyang Liu, X Ma, James Bailey, Hongyuan Zha, Le Song, Shu-tao Xia
Conference Proceedings | 2018 | 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition
Large-scale datasets possessing clean label annotations are crucial for training Convolutional Neural Networks (CNNs). However, la..
Characterizing Adversarial Subspaces Using Local Intrinsic Dimensionality
X Ma, Bo Li, Yisen Wang, Sarah M. Erfani, Sudanthi Wijewickrema, Grant Schoenebeck, Dawn Song, Michael E Houle, james Bailey
Conference Proceedings | 2018 | 6th International Conference on Learning Representations, ICLR 2018 - Conference Track Proceedings
Deep Neural Networks (DNNs) have recently been shown to be vulnerable against adversarial examples, which are carefully crafted in..
Providing automated real-time technical feedback for virtual reality based surgical training: Is the simpler the better?
S Wijewickrema, X Ma, P Piromchai, R Briggs, J Bailey, G Kennedy, S O Leary
Conference Proceedings | 2018 | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
© Springer International Publishing AG, part of Springer Nature 2018. In surgery, where mistakes have the potential for dire conse..
Providing effective real-time feedback in simulation-based surgical training
X Ma, S Wijewickrema, Y Zhou, S Zhou, S O Leary, J Bailey
Conference Proceedings | 2017 | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
© Springer International Publishing AG 2017. Virtual reality simulation is becoming popular as a training platform in surgical edu..
Adversarial generation of real-time feedback with neural networks for Simulation-based training
X Ma, S Wijewickrema, S Zhou, Y Zhou, Z Mhammedi, S O'Leary, J Bailey
Conference Proceedings | 2017 | IJCAI International Joint Conference on Artificial Intelligence
Simulation-based training (SBT) is gaining popularity as a low-cost and convenient training technique in a vast range of applicati..
Design and Evaluation of a Virtual Reality Simulation Module for Training Advanced Temporal Bone Surgery
Sudanthi Wijewickrema, Bridget Copson, Yun Zhou, Xingjun Ma, Robert Briggs, James Bailey, Gregor Kennedy, Stephen O'Leary
Conference Proceedings | 2017 | 2017 IEEE 30th International Symposium on Computer-Based Medical Systems (CBMS)
Unbiased multivariate correlation analysis
Y Wang, S Romano, V Nguyen, J Bailey, X Ma, ST Xia
Conference Proceedings | 2017 | 31st AAAI Conference on Artificial Intelligence, AAAI 2017
Copyright © 2017, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved. Correlation meas..
Research Fellow In Data Mining
Computing And Information Systems
Computing And Information Systems
Doctor of Philosophy
The University of Melbourne
Doctor of Philosophy
University of Melbourne