Welcome to the webpage of the ML & Optimisation reading group! We are interested in a number of broad topics in machine learning and optimisation including (but not limited to):

• Functional Approximators (NN) & Compression Techniques
• Deep Generative Models
• Dynamical Systems
• Gaussian Processes
• Bayesian Optimisation

We meet every Wednesday 10:00-11:00 in MB2.22.

In Term 2-3 we plan to cover the following

1. Generalization, optimization, diverse generation: insights and advances in the use of bootstrapping in deep neural networks, E. BengioLink opens in a new window
2. Data Reduction Algorithms in Machine Learning and Data Science, B. GhojoghLink opens in a new window
3. Provable Algorithms for Machine Learning Problems, R GeLink opens in a new window
4. Neural Transfer Learning for Natural Language Processing, S RuderLink opens in a new window

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Date	Paper/Text book	Chapters	Presenter
18/01/23	Organisational meeting
25/01/23	Generalization, optimization, diverse generation: insights and advances in the use of bootstrapping in deep neural networks, E. BengioLink opens in a new window	Chapter 1-2	Anna Kuchko
01/02/23		Chapter 3	Matthew Keyworth
08/02/23		Chapter 4	Claudia Viaro
15/02/23		Chapter 5	László Udvardi
22/02/23		Chapter 6	Anna Kuchko
	Mid-term pub

If you would like to get engaged in the reading group and present a topic of your interest (or your research if it aligns with the thematics of the reading group) or a paper you have been reading, please contact us.

In AY 2022-2023 the reading group is organised by Claudia Viaro, Anna Kuchko and Laszlo Udvardi. Please don't hesitate to contact us if you have any questions or suggestions!

The information about previous meetings of the reading group can be found here.