Mu Li

Ph.D. student
Computer Science Department
Carnegie Mellon University

Advisors: Alex Smola and Dave Andersen

muli@cs.cmu.edu
Google Scholar
Github

Thesis

• Scaling Distributed Machine Learning with System and Algorithm Co-design
  Thesis Committee: Dave Andersen, Jeff Dean, Barnabas Poczos, Ruslan Salakhutdinov and Alex Smola
  draft, slides: pdf, pdf with animation, keynote

Preprint

• Graph Partitioning via Parallel Submodular Approximation to Accelerate Distributed Machine Learning
  Mu Li, Dave Andersen, Alex Smola
  arxiv

Papers

• AdaDelay: Delay Adaptive Distributed Stochastic Convex Optimization
  Suvrit Sra, Adams Yu, Mu Li, Alex Smola
  In International Conference on Artificial Intelligence and Statistics (AISTATS), 2016
  arxiv
• MXNet: A Flexible and Efficient Machine Learning Library for Heterogeneous Distributed Systems
  Tianqi Chen, Mu Li, Yutian Li, Min Lin, Naiyan Wang, Minjie Wang, Tianjun Xiao, Bing Xu, Chiyuan Zhang, and Zheng Zhang
  In NIPS Workshop on Machine Learning Systems (LearningSys), 2016
  project, paper, GTC'16 slides keynote (with video), pdf
• DiFacto — Distributed Factorization Machines
  Mu Li, Ziqi Liu, Alex Smola, and Yu-Xiang Wang
  In ACM International Conference on Web Search and Data Mining (WSDM), 2016
  pdf, slides, project (Best Paper Honorable Mention)
• Cuckoo Linear Algebra
  Li Zhou, Dave Andersen, Mu Li and Alex Smola
  In ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2015
  paper
• Empirical Evaluation of Rectified Activations in Convolutional Network
  Bing Xu, Naiyan Wang, Tianqi Chen, Mu Li
  ICML Deep Learning Workshop, 2015
  paper
• Inferring Movement Trajectories from GPS Snippets
  Mu Li, Amr Ahmed and Alex Smola
  In ACM International Conference on Web Search and Data Mining (WSDM), 2015
  paper, slides
• Communication Efficient Distributed Machine Learning with the Parameter Server
  Mu Li, Dave Andersen, Alex Smola, and Kai Yu
  In Neural Information Processing Systems (NIPS), 2014
  paper, NIPS OPT workshop paper
• Scaling Distributed Machine Learning with the Parameter Server
  Mu Li, Dave Andersen, Alex Smola, Junwoo Park, Amr Ahmed, Vanja Josifovski, James Long, Eugene Shekita, Bor-Yiing Su
  In Operating Systems Design and Implementation (OSDI), 2014
  paper, 20min slides, 30min slides, NIPS biglearn worshop paper
  
• Efficient Mini-batch Training for Stochastic Optimization
  Mu Li, Tong Zhang, Yuqiang Chen, and Alex Smola
  In ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2014
  paper, slides
• Iterative Row Sampling
  Mu Li, Gary L. Miller, and Richard Peng
  In IEEE Symposium on Foundations of Computer Science (FOCS), 2013
  paper
• Time and Space Efficient Spectral Clustering via Column Sampling
  Mu Li, Xiao-Chen Lian, James Kwok, and Bao-Liang Lu
  In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2011
  paper
• Large-scale Nystrom kernel matrix approximation using randomized SVD
  Mu Li, Wei Bi, James Kwok, and Bao-liang Lu
  In IEEE Transactions on Neural Networks and Learning Systems (TNNLS)
  paper, ICML'14 paper
• Making Large-Scale Nyström Approximation Possible
  Mu Li, James Kwok, and Bao-Liang Lu
  In International Conference on Machine Learning (ICML), 2010
  paper, project
• Online multiple instance learning with no regret
  Mu Li, James Kwok, and Bao-Liang Lu
  In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2010
  paper
• Emotion Classification Based on Gamma-band EEG
  Mu Li and Bao-Liang Lu
  In IEEE Engineering in Medicine and Biology Society (EMBC), 2009
  paper
• Estimating Vigilance in Driving Simulation Using Probabilistic PCA
  Mu Li, Jia-wei Fu, and Bao-Liang Lu
  In IEEE Engineering in Medicine and Biology Society (EMBC), 2008
  paper

Working Experience

• Principal Architect, Baidu, 2014 -
• Intern, Google Research, Summer 2013
• Senior Research and Developer, Baidu, 2011 - 2012
• Research Assistant, Hong Kong University of Science and Technology, 2009 - 2010
• Intern, Microsoft Research Asia, Summer 2007

Teaching

• Lecturer, Machine Learning Summer School, 2014, CMU
• TA of 10-701: Introduction to Machine Learning, Spring 2013, CMU
• TA of Machine Learning, Summer 2010, Shanghai
• Lecturer, Database Management System Project for ACM Honored Class, Spring 2008
• Lecturer, Operating System Project for ACM Honored Class, Fall 2007
• Lecturer, Compiler Project for ACM Honored Class, Spring 2007