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
- Generalization, optimization, diverse generation: insights and advances in the use of bootstrapping in deep neural networks, E. BengioLink opens in a new window
- Data Reduction Algorithms in Machine Learning and Data Science, B. GhojoghLink opens in a new window
- Provable Algorithms for Machine Learning Problems, R GeLink opens in a new window
- Neural Transfer Learning for Natural Language Processing, S RuderLink opens in a new window
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|25/01/23||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|
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.
The information about previous meetings of the reading group can be found here.