This is the reading group of the MEG lab at the Martinos Center.
- When : Alternate Wednesdays, 2 to 3 pm EST
- Where: Zoom (contact us for the link)
- What : Elements of Statistical Learning II
Chapter 2: Overview of supervised learning
Presented by Anish
Chapter 3: Linear methods for regression
11th March 2020
Presented by Isil Uluc
[presentation]
Chapter 4: Linear methods for classification
8th April 2020 and 22nd April 2020
Presented by John Samuelsson
[notes]
Chapter 5: Basis expansion and regularization
5th May 2020
Presented by Ruben Dorfel
[presentation]
[notebook]
Chapter 6: Kernel smoothing methods
10th June 2020
Presented by Kaisu Lankinen
[presentation]
Chapter 7: Model assessment and selection
24th June 2020
Presented by Padma Sundaram
[presentation]
Chapter 11: Neural networks
8th July 2020
Presented by Adonay Nunes
[presentation]
Chapter 8: Model inference and averaging
5th August 2020
Presented by Mainak Jas
[presentation]
Chapter 9: Additive models, trees, and related methods
Natalia Kozhemiako
Chapter 13: Prototype methods and Nearest-Neighbors
Tori Turpin
Chapter 14: Unsupervised learning
Gabriel Motta
Chapter 15: Random forests
Fahimeh Mamashli