Xiaomin Zhang

Address: University of Wisconsin Madison, Department of Computer Sciences. 330 North Orchard Street, Wisconsin Institute for Discovery, Room 3160F.

Biography and Research Interests

I received my PhD degree in Computer Sciences from UW-Madison. I was fortunate to be advised by Professor Po-Ling Loh and Professor Yingyu Liang. My research interests include general machine learning, robust statistics, optimization and differential privacy. I finished my Master's degree in CS Department, UW-Madison as well. I received my Bachelor's degree from Honors College of Beihang University (BUAA). My major was control theory and I got a second degree in Math.

Publications and Patents

Yifu Chen, Christos T. Maravelias, Xiaomin Zhang. Tightening Discretization-based MILP Models for the Pooling Problem using Upper Bounds on Bilinear Terms. Preprint.

Xiaomin Zhang, Xucheng Zhang, Po-Ling Loh, Yingyu Liang. On the Identifiability of Mixtures of Ranking Models. [arXiv]

Jinman Zhao, Shawn Zhong, Xiaomin Zhang, Yingyu Liang. PBoS: Probabilistic Bag-of-Subwords for Generalizing Word Embedding. Findings of EMNLP 2020. [arXiv]

Xiaomin Zhang, Xiaojin Zhu, Po-Ling Loh. Provable Training Set Debugging for Linear Regression. ECML PKDD 2021 Journal Track. [arXiv]

Xiaomin Zhang, Haibin Duan, Chen Yang. [Best Paper Award] Pigeon-Inspired Optimization Approach to Multiple UAVs Formation Reconfiguration Controller Design. Proceedings of 2014 IEEE Chinese Guidance, Navigation and Control Conference, 8-10 August 2014, Yantai, China, pp.2707-2712.

Zhang X.; Chen Y.; Li G.; Sun X.; Lin W.; Liu L.; Ma K.; Xuan Z.; Zhao Y.; Predition-based System and Method For Trajectory Planning of Autonomous Vehicles, 2019, WO2019051511, March 14, 2019.

Zhang X.; Chen Y.; Li G.; Sun X.; Lin W.; Liu L.; Ma K.; Xuan Z.; Zhao Y.; Predition-based System and Method For Trajectory Planning of Autonomous Vehicles, 2019, WO2019060927, March 28, 2019.

Teaching Experiences

CS 240 [TA]: Introduction to Discrete Mathematics, FA15, FA21.

CS 524 [TA]: Introduction to Optimization, SP16, SP19, FA19, FA20.

CS 526 [TA]: Advanced Linear Programming, SP20.

CS 532 [TA]: Matrix Methods in Machine Learning, FA 16.

CS 540 [TA]: Introduction to Artificial Intelligence, SP 17.

CS 761 [TA]: Advanced Machine Learning, FA 17.

Activities

Sep. 2021, attended ECML PKDD 2021 Virtual Conference.

Jun. 2020, attended STOC 2020 Virtual Symposium.

Jul. 2018, attended IFDS workshop, Madison.

Jun. 2018, attended Midwest ML Symposium, Chicago.

Apr. 2018, attended Statistical Scalability Workshop, Windermere.

Mar. 1 2018, invited talk, Intelligent Systems Laboratory at the University of Bristol, Bristol.

Feb.-Mar. 2018, participated in Statistical Scalability Programme in Isaac Newton Institute, Cambridge.

Feb. 2018, attended Robust Statistics Workshop in Erasmus School of Economics, Rotterdam.

Sep. 22 2016, took over a class for Prof. Lessard, Madison.

Selected Reports

Lower PAC bound on Upper Confidence Bound-based Q-learning with examples. [pdf]

Low Resolution Facial Landmark Detection with Improved Convolutional Neural Network. [pdf]

Image Inpainting via Sparse Representation over Online Dictionary. [pdf]