Data, Environments, and Learners: Theory and Algorithms

Research Group at UCL Statistical Science

Led by Omar Rivasplata

IMSS Fellow

Top-level areas of interest
AI.   Machine Learning.   Statistical Learning Theory.   Mathematics.   Probability and Statistics.  

What is this research group about?
The group's mission is solving optimisation and certification problems for machine learning algorithms.

We are interested in sound theory that helps to understand the performance (optimisation, generalisation) of machine learning algorithms. Most notably (but not only) we are interested in deep learning algorithms which are highly relevant nowadays since neural networks are important components of many modern algorithmic learning systems.

Our approach consists of leveraging mathematics, statistics, and computer experiments, to obtain meaningful knowledge about these algorithms and to inform better design choices. Particulary, we aim to develop learning and certification strategies that make efficient use of the available data and deliver reliable performance guarantees.

Prospective students
Please reach out to the group lead to enquire.

Past students
  • Luo Zhen, MSc Data Science (Summer 2023).
  • Sharmilan Ilankesan, MSc Statistical Science (Summer 2023).
  • Carlos Pita Amerigo, MSc Mathematics (2022/23).
  • Qinyi Wu, MSc Mathematics (2022/23).
  • Yousef Nami, MSc Computational Statistics and Machine Learning (Summer 2022).
  • Qingyu Feng, MSc Computational Statistics and Machine Learning (Summer 2022).


Please reach out to the group lead to enquire.

DELTA talks - Season 1

DELTA talks - Season 2

Machine Learning Links
What is machine learning?
Understanding Machine Learning
Rich Sutton's incomplete ideas (and RL resources)
Robert Duin's 37 steps (and PR tools and blog)
Advice for Machine Learning students

Math Links
What's new (Terry Tao's blog)
Maths Research Seminars (beta).
The complex number operations neatly visualised.
Advice for Math students

Probability Links (probably accessible)
Almost Sure
Research in Probability
The Gaussian Processes Website
Advice for Probability students

Stats Links (most significant)
Random stuff
Frequentism and Bayesianism
Advice for Stats students

Writing aids
How to Write Mathematics, tips from the Mathematics Student Handbook at Trent University.
A Guide to Writing Mathematics by Kevin Lee.
Writing Mathematics by Berry & Lawson.
The Underground Grammarian by Richard Mitchell.