Jason D Lee

Jason D Lee Ph.D. Candidate jdl17(AT)stanford(DOT)edu Institute of Computational and Mathematical Engineering (iCME) Stanford University

Research Interests

• Statistics (Statistical Learning and High-dimensional Statistics)
  

• Machine Learning
  

• Optimization

Publications

• Learning Mixed Graphical Models
  Jason D Lee, Trevor Hastie, AISTATS 2013.
  Extended version available on arXiv. Project Homepage.

• Proximal Newton-type Methods for Minimizing Convex Objective Functions in Composite Form
  Jason D Lee, Yuekai Sun and Michael Saunders, NIPS 2012.
  Extended version on arXiv. PNOPT package homepage.

• Analysis of Inexact Proximal Newton-type Methods
  Jason D Lee, Yuekai Sun, and Michael Saunders, NIPS 2012 Optimization and Machine Learning Workshop.
  

• Practical Large Scale Optimization for Max-norm Regularization
  Jason D Lee, Benjamin Recht, Ruslan Salakhutdinov, Nati Srebro, and Joel Tropp, NIPS 2010.

• Multiscale Dynamic Graphs
  Jason D Lee and Mauro Maggioni, Sampling Theory and its Applications 2011.

• Multiscale Analysis of Graph Time Series
  Jason D Lee and Mauro Maggioni, In Preparation.

• Generalized DCell Structure for Load-Balanced Data Center Networks
  Markus Kliegl, Jason D Lee, Jun Li, Xinchao Zhang, Chuanxiong Guo, and David Rincon, IEEE Infocom 2010.

• Estimation of intrinsic dimensionality of samples from noisy low-dimensional manifolds in high dimensions with multiscale SVD
  Anna V. Little, Jason D Lee, and Mauro Maggioni, IEEE Statistical Signal Processing Workshop 2009.

Other Publicatons

• Learning Structured Matrices
  Jason D Lee, Carlos Sing-Long, and Yuekai Sun, Class Project for Discrete Math and Advanced Topics in Convex Optimization
  

• Multiscale Estimation of Intrinsic Dimensionality of Point Cloud Data and Multiscale Analysis of Dynamic Graphs
  Jason D Lee, Advisor: Mauro Maggioni, Awarded Graduation with High Distinction.

• The Generalized DCell Network Structures and Their Graph Properties
  Markus Kliegl, Jason Lee, Jun Li, Xinchao Zhang, Chuanxiong Guo, and David Rincon, Microsoft Research Technical Report, October 2009.

• Existence of Asymptotic Solutions to Semilinear Partial Difference Equations on Graphs
  Jason D Lee and John Neuberger, AMS-MAA Joint Mathematics Meetings 2008.

Education

• PhD, Computational and Mathematical Engineering, Stanford University, September 2010-Present.

• BS with High Distinction (Magna Cum Laude), Mathematics, Duke University, May 2010.

• Lynbrook High School, San Jose, California, June 2006.

Experience

• Intern at Machine Learning Department, Microsoft Research Redmond, June-September 2012.
  Mentor: Ran Gilad-Bachrach
  Project: Provable methods for clustering.

• Intern at Microsoft Research Redmond, Internet Services Research Center, June-September 2011.
  Mentor: Emre Kiciman
  Project: Distributed optimization for matrix factorizations.

• Intern at Toyota Technology Institute- Chicago, May-September 2010.
  Mentor: Nati Srebro
  Project: Large-scale optimization for max-norm regularization with applications to collaborative filtering, matrix completion, clustering and inference in Markov random fields.

• PRUV Fellow and Senior Thesis Research, Duke University, June 2009-May 2010.
  Mentor:Mauro Maggioni
  Project: Multiscale estimation of intrinsic dimensionality of point cloud data and multiscale analysis of dynamic graphs.

• Intern at Microsoft Research Asia Wireless and Networking Group, May-August 2009.
  Mentors:Chuanxiong Guo and David Rincon
  Project: Properties of generalized DCell data center network.

Awards

• NSF Graduate Fellowship in Applied Mathematics

• National Defense Science and Engineering Graduate Fellowship

• Stanford Graduate Fellowship

• Julia Dale Prize in Mathematics, Duke 2010.

• Phi Beta Kappa