UNSW Computational Statistics / Machine Learning  Reading Group
Each session ,the person leading the session will prescribe some reading (to be read beforehand), and during the session will lead a discussion about the material. 

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Due to the current situation, these sessions are on hold indefinitely.

Future Sessions 

Theme: Optimal Transport

Why are we looking at this stuff?  See this brief Discussion Paper on Applications in Methodological Statistics/Machine Learning  (we will look at some of the things mentioned in Part II).

Part I: Foundations

Friday 13th March, 11AM — Rob Salomone
Location: Business School 130
Reading: pp. 1-30 of the Book (resp. pp. 1–15 of Course Notes)

Topic: Entropic Regularization & Sinkhorn Iteration 
Topic: Wasserstein Barycenters & Wasserstein Estimation (Xuhui) 
Topic: Gradient Flows (Spiro)

Gery Geenens
Yu Guang Wang
Yu Yang
Matt Gibson
Dan Mackinlay

Part II: Methodological/Related Papers


Course Notes 

Past Sessions

Theme: Variational Autoencoders (and Related Topics)

17th September, 2019 — Rob Salomone 
 2nd October, 2019 — Boris Beranger
16th October, 2019 — Xuhui Fan
  23rd October, 2019 — Dan Mackinlay
6th November, 2019 —  Yu Guang Wang