mathurinm / andersoncdLinks
This code is no longer maintained. The codebase has been moved to https://github.com/scikit-learn-contrib/skglm. This repository only serves to reproduce the results of the AISTATS 2021 paper "Anderson acceleration of coordinate descent" by Quentin Bertrand and Mathurin Massias.
☆18Updated 2 years ago
Alternatives and similar repositories for andersoncd
Users that are interested in andersoncd are comparing it to the libraries listed below
Sorting:
- El0ps: An Exact L0-Problem Solver☆11Updated 3 weeks ago
- Fast hyperparameter settings for non-smooth estimators:☆40Updated 2 years ago
- ☆13Updated 4 months ago
- Python package to fetch data from the LIBSVM website.☆20Updated 2 months ago
- Proximal optimization in pure python☆118Updated 3 years ago
- Probabilistic ODE solvers are fun, but are they fast? See also: https://github.com/pnkraemer/probdiffeq for JAX code or https://github.c…☆21Updated 11 months ago
- Source code for my PhD thesis: Backpropagation Beyond the Gradient☆20Updated 2 years ago
- PEPit is a package enabling computer-assisted worst-case analyses of first-order optimization methods.☆88Updated 5 months ago
- An ultra-lightweight JAX implementation of sparse Gaussian processes via pathwise sampling.☆22Updated 4 years ago
- Kernel Stein Discrepancy Descent : a method to sample from unnormalized densities☆21Updated last year
- Code for the paper "Randomly pivoted Cholesky: Practical approximation of a kernel matrix with few entry evaluations"☆29Updated 8 months ago
- Painless optimisation of constrained variables in AutoGrad, TensorFlow, PyTorch, and JAX☆23Updated 2 years ago
- Anderson accelerated Douglas-Rachford splitting☆29Updated 4 years ago
- Code for the Paper "Physics-Informed Gaussian Process Regression Generalizes Linear PDE Solvers"☆30Updated last year
- ☆26Updated 5 months ago
- Implementation for Non-stationary Spectral Kernels (NIPS 2017)☆20Updated 5 years ago
- Non-stationary spectral mixture kernels implemented in GPflow☆28Updated 6 years ago
- A Python library for mathematical optimization☆141Updated 9 months ago
- Riemannian Optimization Using JAX☆49Updated last year
- Chirp instantaneous frequency estimation using stochastic differential equation Gaussian processes☆12Updated 8 months ago
- Benchopt benchmark for Lasso☆14Updated last year
- Conditional density estimation with neural networks☆31Updated 5 months ago
- Fully Bayesian Inference in GPs - Gaussian and Generic Likelihoods☆22Updated last year
- PyProximal – Proximal Operators and Algorithms in Python☆68Updated 4 months ago
- Tutorial materials of the Probabilistic Numerics Spring School.☆34Updated 2 years ago
- Public code for running Stochastic Gradient Descent on GPs.☆39Updated 2 months ago
- A LinearOperator implementation to wrap the numerical nuts and bolts of GPyTorch☆111Updated 3 months ago
- Gradient-informed particle MCMC methods☆12Updated last year
- Code for ICML 2019 paper on "Fast and Simple Natural-Gradient Variational Inference with Mixture of Exponential-family Approximations"☆18Updated 4 years ago
- Solves the best subset selection problem☆44Updated 3 years ago