Selective Inference is the problem of testing hypotheses that are chosen or suggested by the
data. Inference after variable selection in high-dimensional linear regression is a common
example of…

Thursday, February 6, 2014 at 4:15pm
Frank H. T. Rhodes Hall, 253
ORIE Colloquium: Po-Ling Loh (Cal-Berkeley) - Nonconvex Methods for High-Dimensional Regression with Noisy and Missing Data
Noisy…

Friday, May 2
2:20 p.m. – Presentation – 253 Rhodes Hall
Philippe Rigollet
The statistical price to pay for computational efficiency in sparse PCA
Computational limitations of…

Computing reliable solutions to inverse problems is important in many applications such as biomedical imaging, computer graphics, and security. Regularization by incorporating prior knowledge is…

ORIE/Statistics Colloquium: Sahand Negahban (MIT) - Structured Estimation in High-Dimensions
Wednesday, February 20, 2013 at 4:15pm
Frank H. T. Rhodes Hall, 253
Modern techniques in data…

CAM Colloquium: Mason Porter (Oxford) - Cascades and Social Influence on Networks
Friday, February 1, 2013 at 3:30pm
Frank H. T. Rhodes Hall, 655
Cascades and Social Influence on NetworksI discuss…

CAM Colloquium: Mason Porter (Oxford) - Cascades and Social Influence on Networks
Friday, February 1, 2013 at 3:30pm
Frank H. T. Rhodes Hall, 655
Cascades and Social Influence on NetworksI discuss…

Tridiagonal matrices appear almost everywhere (like 2nd order differential operators).This talk grew out of four very different applications: 1. (positive definite) Completion to maximum…