Haichuan Yang
Haichuan Yang

Bio:

I am currently a PHD student (since 2015) at Department of Computer Science, University of Rochester, Rochester, N.Y. My advisor is Prof. Ji Liu. Before that, I received the bachelor's degree in 2012 in Software Engineering from Sun Yat-sen University, Guangzhou, China and the master's degree in 2015 in Computer Science and Engineering from Beihang University, Beijing, China. My current research interests focus on machine learning, particularly in deep neural network compression, feature selection, sparse optimization and reinforcement learning. HERE is my CV.

Selected Publications

Conference Papers

  • ECC: Platform-Independent Energy Constrained Deep Neural Network Compression via a Bilinear Regression Model.
    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.[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.
    Eisenach, C.,* Yang, H.*, Liu, J. & Liu, H. (* Equal contribution)
    In International Conference on Learning Representations (ICLR), 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:
    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 Travel Award, 2019
  • Outstanding Master Dissertation Award of Beihang University, 2015
  • Chinese National Scholarship, 2014
  • Google Excellence Scholarship, 2014

Contact:

Office:3207, Wegmans Hall
E-mail: hyang36 A.T. cs.rochester.edu

Department of Computer Science
University of Rochester
Rochester, NY 14627