| Date | Speaker | Topic (slides) |
|---|---|---|
| 13 Jan | Ed Bueler | Getting started on machine learning |
| 20 Jan | Ed Bueler | Getting started on machine learning cont. planning discussion |
| 27 Jan | Liam Toney (and Ed) | laptop day: Try actual ML computations! I'll show how to run Matlab codes. Anyone can show how to get started on any ML example in their preferred environment (e.g. R, PyTorch, Tensorflow, ...). |
| 3 Feb | Glen Woodworth | convolutions and convolutional neural nets |
| 10 Feb | Stefano Fochesatto | decision tree learning from scratch |
| 17 Feb | Austin Smith | perceptrons and XOR |
| 24 Feb | Nathan Barnes | autoencoders |
| 3 Mar | Kyungmin Kim | support vector machines |
| 17 Mar | Ed Bueler | online optimization |
| 24 Mar | Kyle Blum | machine learning in ice sheet modeling |
| 31 Mar | Oscar Hernandez | universal approximation and the efficiency of depth |
| 7 Apr | Gabrielle Nowak | graph neural networks |
| 14 Apr | Blake Mino | biological motivations of artificial neural networks |
| 21 Apr | Stefan Awender | recognizing digits with a neural network |