Jason D Lee
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Jason D Lee |
Research Interests
Machine Learning
Optimization
Statistics
Multiscale Analysis
Signal Processing
Current Work
Structure Learning of Graphical Models with Professor Trevor Hastie
Contact Information
Huang Building, 475 Via Ortega, Stanford University
Recent Publications
Practical Large Scale Optimization for Max-norm Regularization
Jason Lee, Benjamin Recht, Ruslan Salakhutdinov, Nathan Srebro, and Joel Tropp, NIPS 2010.Multiscale Dynamic Graphs
Jason Lee and Mauro Maggioni, Sampling Theory and its Applications 2011.Multiscale Analysis of Graph Time Series
Jason Lee and Mauro Maggioni, In Preparation.Generalized DCell Structure for Load-Balanced Data Center Networks
Markus Kliegl, Jason 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 Lee, and Mauro Maggioni, IEEE Statistical Signal Processing Workshop 2009.
Other Publicatons
Learning Structured Matrices
Jason Lee, Carlos Sing-Long, and Yuekai Sun, Class Project for Discrete Math and Advanced Topics in Convex OptimizationMultiscale Estimation of Intrinsic Dimensionality of Point Cloud Data and Multiscale Analysis of Dynamic Graphs
Jason 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 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 Microsoft Research Redmond, Internet Services Research Center, Mentor: Emre Kiciman, June 2011-Present.
Intern at Toyota Technology Institute- Chicago, Mentor: Nati Srebro, Research on Large-Scale Optimization for Max-Norm Regularization with Applications to Machine Learning: Collaborative Filtering, Matrix Completion, Clustering and Inference in Markov Random Fields, May-September 2010.
PRUV Fellow and Senior Thesis Research, Duke University, Multiscale Estimation of Intrinsic Dimensionality of Point Cloud Data and Multiscale Analysis of Dynamic Graphs, Advisor: Mauro Maggioni, June 2009-May 2010.
Joint Research Program between Microsoft Research Asia Wireless and Networking Group and UCLA Institute for Pure and Applied Math (IPAM), Properties of Generalized DCell Data Center Network, Advisor: Chuanxiong Guo and David Rincon, May-August 2009.
REU (Research Experience for Undergraduates) at Rutgers University DIMACS and Charles University in Prague, Advisor: Aaron Jaggard, Conducted research on Pattern Avoidance in Permutations and Involutions and participated in the Midsummer Combinatorics Workshop at Charles University, Summer 2008.
REU (Research Experience for Undergraduates) at Northern Arizona University, Advisor: John. Neuberger, Semilinear Partial Differential Equations using Variational Principles, Summer 2007.
Participant in the Institute of Advanced Study-Park City Math Institute in Image Processing, Summer 2010.