Writing on machine learning, statistics, optimisation and programming.
Recent writing
All posts-
Optimisation Under Uncertainty Part 2: An LP reformulation aside
A slight diversion: how to reformulate a linear program with a nested maximisation using duality
-
Optimisation Under Uncertainty Part 1: Murphy's Law
Introduction to robust optimisation under uncertainty. Part 1 covers theoretical foundations and the trade-offs between optimality and robustness.
-
Building Non-Standard Regression Models with JAX
Using JAX's automatic differentiation to train a Zero-Inflated Generalised Poisson regression model
-
Online Bayesian Learning Part 4: Non-stationary data and R-VGA
Adapting R-VGA to work in non-stationary environments.
-
Online Bayesian Learning Part 3: R-VGA
Deriving and implementing the R-VGA algorithm for online learning with neural networks on streaming binary classification data
-
Online Bayesian Learning Part 2: Bayesian Neural Networks With Variational Inference
A quick detour to introduce variational inference and use it to train a small Bayesian neural network with jax/eqx
-
Online Bayesian Learning Part 1: Exact recursive inference
Part 1 of a series of posts looking into the problem of 'online' learning using Bayesian methods
-
C++20: SFINAE vs. Concepts
Comparing C++20 Concepts with SFINAE for template constraints. Modern approaches to type checking and compile-time validation.