Tianwei Xing [PhD Student]
image

NESL

Electrical Engineering

Lab: 1762 Boelter Hall
UCLA Main Campus

Mail:
UCLA
EE Department
420 Westwood Plaza
MC# 951594
Los Angeles, CA 90095-1594
ATTN: 56-125KK, EEIV
C/O: Fe Asuncion

Email:
twxing@ucla.edu

Tel [work]:
424-324-0431

Education:

Research Interests:

  • Deep Learning: network compression and acceleration, distributed learning, transfer learning.
  • Machine Learning: Statistical Modeling and Inference
  • Ubiquitous Computing

Recent Publications:

  • Why the Failure? How Adversarial Examples Can Provide Insights for Interpretable Machine Learning
    Richard Tomsett, Amy Widdicombe, Tianwei Xing, Supriyo Chakraborty, Simon Julier, Prudhvi Gurram, Raghuveer Rao, and Mani B. Srivastava.
    21st International Conference on Information Fusion (FUSION 2018), October 2018. [ Details ]
  • Enabling Edge Devices that Learn from Each Other: Cross Modal Training for Activity Recognition
    Tianwei Xing, Sandeep Singh Sandha, Bharathan Balaji, Supriyo Chakraborty, and Mani B. Srivastava.
    1st International Workshop on Edge Systems, Analytics and Networking (EdgeSys 2018), June 2018. [ Details ]
  • Deep Learning for Situational Understanding
    Supriyo Chakraborty, Alun Preece, Moustafa Alzantot, Tianwei Xing, Dave Braines, and Mani B. Srivastava.
    20th International Conference on Information Fusion, June 2017. [ Details ]
  • Binarized Neural Networks with Separable Filters
    Jeng-Hau Lin, Tianwei Xing, Ritchie Zhao, Mani B. Srivastava, Zhiru Zhang, Rajesh K. Gupta, and Zhuowen Tu.
    Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), May 2017. [ Details ]
  • Accelerating Binarized Convolutional Neural Networks with Software-Programmable FPGAs
    Ritchie Zhao, Weinan Song, Wentao Zhang, Tianwei Xing, Jeng-Hau Lin, Mani B. Srivastava, Rajesh K. Gupta, and Zhiru Zhang.
    International Symposium on Field-Programmable Gate Arrays (FPGA), February 2017. [ Details ]

Other Publications:

  • Jie Xu, Tianwei Xing and Mihaela van der Schaar, "Personalized Course Sequence Recommendations” IEEE Transactions on Signal Processing, vol. 64, no. 20, pp. 5340-5352, Oct. 2016.

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