Convergence rates of biased stochastic optimization for learning sparse ising models
J Honorio - arXiv preprint arXiv:1206.4627, 2012 - arxiv.org
We study the convergence rate of stochastic optimization of exact (NP-hard) objectives, for
which only biased estimates of the gradient are available. We motivate this problem in the …
which only biased estimates of the gradient are available. We motivate this problem in the …
[PDF][PDF] 1 Teaching
L El Ghaoui - people.eecs.berkeley.edu
EECS 120. I have taught this course once, and found it extremely challenging. I do not like
the material, which I believe is too fixated on minute details of Fourier transforms. On the …
the material, which I believe is too fixated on minute details of Fourier transforms. On the …
Tractable learning of graphical model structures from data
JFH Carrillo - 2012 - search.proquest.com
Probabilistic graphical models (PGMs) provide a way to represent variables (nodes) along
with their conditional dependencies (edges) and therefore allow formalizing our knowledge …
with their conditional dependencies (edges) and therefore allow formalizing our knowledge …
Advances in statistical methodology and analysis in a study of ARC syndrome
AM Lyne - 2016 - discovery.ucl.ac.uk
This thesis presents statistical analysis and methodology development for a systems
analysis of ARC syndrome. ARC is a genetic disease caused by mutations in one of two …
analysis of ARC syndrome. ARC is a genetic disease caused by mutations in one of two …
Ben Rolfs Stats 375 Project Proposal, 1/17/2011 We are interested in log-determinant relaxations for approximating the marginalization problem for Markov random …
S Bacallado - stanford.edu
Sergio Bacallado Ben Rolfs Stats 375 Project Proposal, 1/17/2011 We are interested in log-determinant
relaxations for approximat Page 1 Sergio Bacallado Ben Rolfs Stats 375 Project Proposal, 1/17/2011 …
relaxations for approximat Page 1 Sergio Bacallado Ben Rolfs Stats 375 Project Proposal, 1/17/2011 …