26 Sep 2024 | A trick to convert classification labels to regression targets and back. #math #ml #code |
18 Mar 2024 | A short note on over-parameterizing the L1 regularizer to make it differentiable #math #ml |
12 Jan 2024 | A simple generalization of Mahalanobis distance to Gaussian Mixture Models (GMMs). #math #ml #code |
04 Aug 2023 | A guide to updating probabilistic beliefs using Jeffrey's rule and Pearl's method. #math #ml #probability |
29 Aug 2022 | Discussion about the MAGSAC algorithm, addressing a crucial hyperparameter selection issue for the RANSAC algorithm. #math #ml #code #jax |
18 Jul 2022 | Two examples of using complex numbers for real-function optimization. #numerics #math #ml #gradient #code #python |
29 Jun 2022 | Stochastic Gradient Descent can be (kind of) reversed and can be used to compute gradients with respect to its hyperparameters. #math #ml #gradient #graph #code #jax #deep-learning |
31 May 2022 | The associative property of Kalman (Bayesian) filters can yield a parallel algorithm in O(log N). #math #ml #parallel #code #jax |
23 Sep 2021 | A quick discussion and a vectorized Python implementation for the computation of sample covariance matrices for multi-dimensional arrays. #math #ml #code |
30 Aug 2021 | A tutorial on the lossless Asymmetric Numeral Systems (ANS) coding commonly used in image compression. #math #ml #information-theory #code |
14 Aug 2021 | A discussion of an argument that no Turing Machine can adequately mimic human cognitive abilities, following Gödel's theorems. #philosophy #ai #math |
28 Jul 2021 | Notes on the book 'Gödel's Proof' by Ernest Nagel and James Newman #math #philosophy #self-referential |
27 Jun 2021 | An interesting connection between the number of cycles in a digraph and its power adjacency matrix leads to a beautiful formulation for DAG constrains. #graph #math #ml |
18 Jun 2020 | Implicit differentiation can lead to an efficient computation of the gradient of reparametrized samples. #math #ml #gradient #deep-learning |
08 Jun 2020 | A trick for interchanging the gradient and Expectation of a function under the Gaussian distribution. #math #ml #gradient #deep-learning |
18 Aug 2019 | A slight change in SGD formulation, in terms of maximization of local approximation, leads to an interesting general connection to NGD via mirror descent. #math #ml #gradient #natural-gradient #deep-learning |
08 Aug 2019 | The Exponential family provides an elegant and easy method to compute Natural Gradients and thus can be used for Variational Inference. #math #ml #gradient #natural-gradient #deep-learning |