Selected Publications
Conference Papers
- Automatic Neural Network Compression by Sparsity-Quantization Joint Learning: A Constrained Optimization-based Approach.[PDF][CODE]
Yang, H., Gui, S., Zhu, Y. & Liu, J.
In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020.
- ECC: Platform-Independent Energy Constrained Deep Neural Network Compression via a Bilinear Regression Model.[PDF][CODE]
Yang, H., Zhu, Y. & Liu, J.
In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019.
- Energy-Constrained Compression for Deep Neural Networks via Weighted Sparse Projection and Layer Input Masking.[PDF][CODE]
Yang, H., Zhu, Y. & Liu, J.
In International Conference on Learning Representations (ICLR), 2019.
- Marginal Policy Gradients: A Unified Family of Estimators for Bounded Action Spaces with Applications.[PDF][CODE]
Eisenach, C.,* Yang, H.*, Liu, J. & Liu, H. (* Equal contribution)
In International Conference on Learning Representations (ICLR), 2019.
- Model Compression with Adversarial Robustness: A Unified Optimization Framework
Gui, S., Wang, H., Yang, H., Yu, C., Wang, Z. & Liu, J.
In Conference on Neural Information Processing Systems (NeurIPS), 2019.
- On The Projection Operator to A Three-view Cardinality Constrained Set.[PDF]
Yang, H., Gui, S., Ke, C., Stefankovic, D., Fujimaki, R., & Liu, J.
In International Conference on Machine Learning (ICML), 2017.
- Online Feature Selection: A Limited-Memory Substitution Algorithm and Its Asynchronous Parallel Variation.[PDF][VIDEO]
Yang, H., Fujimaki, R., Kusumura, Y., & Liu, J.
In ACM SIGKDD Conferences on Knowledge Discovery and Data Mining (SIGKDD), 2016.
- On Benefits of Selection Diversity via Bilevel Exclusive Sparsity.[PDF]
Yang, H., Huang, Y., Tran, L., Liu, J., & Huang, S.,
In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016.
- Semi-randomized Hashing for Large Scale Data Retrieval.[PDF]
Yang, H., Bai, X., Zhou, J., Ren, P., Cheng, J., & Lu, B.,
In International Conference on Data Science and Advanced Analytics (DSAA), 2014
- Adaptive Object Retrieval with Kernel Reconstructive Hashing.[PDF][CODE]
Yang, H., Bai, X., Zhou, J., Ren, P., Zhang, Z., & Cheng, J.,
In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2014.
- Label Propagation Hashing Based on p-stable Distribution and Coordinate Descent.[PDF]
Yang, H., Bai, X., Liu, C., & Zhou, J.,
In IEEE International Conference on Image Processing (ICIP), 2013
Journal Articals
- Robust AUC Maximization Framework With Simultaneous Outlier Detection and Feature Selection for Positive-Unlabeled Classification.
Ren, K.,* Yang, H.*, Zhao, Y., Chen, W., Xue, M., Miao, H., Huang, S. & Liu, J. (* Equal contribution)
IEEE Transactions on Neural Networks and Learning Systems, 2018.
- Maximum Margin Hashing with Supervised Information.
Yang, H., Bai, X., Liu, Y., Wang Y., Bai, L., Zhou, J., & Tang, W.,
Multimedia Tools Appl., volume 75, pp. 3955-3971, 2016.
- Data-dependent Hashing Based on p-Stable Distribution.[PDF][CODE]
Bai, X., Yang, H., Zhou, J., Ren, P., & Cheng, J.,
IEEE Transactions on Image Processing, 2014 23(12): 5033-5046.
Services
- Reviewer:
AAAI-2020, NeurIPS-2019, ICCV-2019, CVPR-2019, AAAI-2019.
- Teaching Assistant:
[2018] CSC 458 - Parallel and Distributed Systems; [2017] CSC 440 - Data Mining; [2016] CSC 576 - Advanced Machine Learning and Optimization.
Honors and awards
- ICLR 2019 Travel Award
- Outstanding Master Dissertation Award of Beihang University
- Chinese National Scholarship
- Google Excellence Scholarship
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