Mark Schmidt
homepage:http://www.cs.ubc.ca/~schmidtm/
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Description

I'm currently a PhD Candidate in the Department of Computer Science at UBC, working in the Laboratory for Computational Intelligence under the supervision of Kevin Murphy. I used to be at the University of Alberta working for the Alberta Ingenuity Centre for Machine Learning under Russ Greiner as part of the Brain Tumor Analysis Project group. In the summer of 2006, I worked with Rómer Rosales and Glenn Fung at the Computer-Aided Diagnosis and Therapy Group at Siemens Medical Solutions.


Lectures:

votesvotesvotesvotesvotes [syn]  7528 views, 1:30:26  
tutorial
flag Smooth, Finite, and Convex Optimization Deep Learning Summer School
as author at  Deep Learning Summer School, Montreal 2015,
7528 views
 
votesvotesvotesvotesvotes [syn]  7427 views, 1:32:19  
tutorial
flag Non Smooth, Non Finite, and Non Convex Optimization
as author at  Deep Learning Summer School, Montreal 2015,
7427 views
votesvotesvotesvotesvotes [syn]  7876 views, 53:13   Invited Talk
 invited talk
flag Limited-memory quasi-Newton and Hessianfree Newton methods for non-smooth optimization
as author at  Optimization for Machine Learning,
7876 views
 
votesvotesvotesvotesvotes [syn]  6887 views, 16:43  
lecture
flag Convergence Rates of Inexact Proximal-Gradient Methods for Convex Optimization
as author at  25th Annual Conference on Neural Information Processing Systems (NIPS), Granada 2011,
6887 views
4061 views, 54:29   Tutorial
 tutorial
flag Modern Convex Optimization Methods for Large-scale Empirical Risk Minimization
as author at  32nd International Conference on Machine Learning (ICML), Lille 2015,
4061 views
 
[syn]  5908 views, 27:36  
lecture
flag Convex structure learning in log-linear models beyond pairwise potentials
as author at  13th International Conference on Artificial Intelligence and Statistics (AISTATS), Sardinia 2010,
5908 views