About
The first UCL-Duke University Workshop on Sensing and Analysis of High-Dimensional Data, which acts as the European counterpart of the Biannual Duke University SAHD Workshop, aims to bring together leading researchers in the general fields of mathematics, statistics, computer science and engineering that work at the intersection of computational statistics, machine learning, signal processing, information and learning theory, and computer science, with the goal to advance the field of sensing, analysis and processing of high-dimensional data.
Videos
Keynote

The Unreasonable Effectivness Of Deep Learning
Oct 29, 2014
·
41120 views
Invited Talks

Breaking the coherence barrier - A new theory for compressed sensing
Oct 29, 2014
·
2759 views

Mondrian forests: Efficient random forests for streaming data via Bayesian nonpa...
Oct 29, 2014
·
8659 views

High-dimensional learning with deep network contractions
Oct 29, 2014
·
10538 views

Building an automatic statistician
Oct 29, 2014
·
4242 views

Beyond stochastic gradient descent for large-scale machine learning
Oct 29, 2014
·
7725 views

Deep Gaussian processes
Oct 29, 2014
·
4647 views

Optimal compressive imaging for Fourier data
Oct 29, 2014
·
2881 views

Tracking dynamic point processes on networks
Oct 29, 2014
·
2258 views

Conjugate gradient iterative hard thresholding for compressed sensing and matrix...
Oct 29, 2014
·
2445 views

Living on the edge: Phase transitions in convex programs with random data
Oct 29, 2014
·
2682 views

Visual pattern encoding on the Poincaré sphere
Oct 29, 2014
·
2459 views
Panel

Big Data - Challenges and Opportunities
Oct 29, 2014
·
2858 views

Welcome
Oct 29, 2014
·
3017 views