mathurinm / andersoncd
This code is no longer maintained.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.
☆17Updated 2 years ago
Alternatives and similar repositories for andersoncd:
Users that are interested in andersoncd are comparing it to the libraries listed below
- Fast hyperparameter settings for non-smooth estimators:☆39Updated last year
- El0ps: An Exact L0-Problem Solver☆9Updated last month
- Anderson accelerated Douglas-Rachford splitting☆29Updated 4 years ago
- ☆13Updated 2 weeks ago
- Source code for my PhD thesis: Backpropagation Beyond the Gradient☆20Updated 2 years ago
- Python package to fetch data from the LIBSVM website.☆20Updated last year
- Probabilistic ODE solvers are fun, but are they fast? See also: https://github.com/pnkraemer/probdiffeq for JAX code or https://github.c…☆20Updated 7 months ago
- PEPit is a package enabling computer-assisted worst-case analyses of first-order optimization methods.☆85Updated last month
- Chirp instantaneous frequency estimation using stochastic differential equation Gaussian processes☆11Updated 4 months ago
- Proximal algorithms made easy in Python☆59Updated 8 years ago
- An ultra-lightweight JAX implementation of sparse Gaussian processes via pathwise sampling.☆22Updated 3 years ago
- Methods and experiments for assumed density SDE approximations☆11Updated 3 years ago
- A generic library for linear and non-linear Gaussian smoothing problems. The code leverages JAX and implements several linearization algo…☆12Updated 3 months ago
- Code for ICML 2019 paper on "Fast and Simple Natural-Gradient Variational Inference with Mixture of Exponential-family Approximations"☆18Updated 4 years ago
- Benchopt benchmark for Lasso☆14Updated last year
- ☆26Updated last month
- Tutorial materials of the Probabilistic Numerics Spring School.☆34Updated last year
- Probabilistic solvers for differential equations in JAX. Adaptive ODE solvers with calibration, state-space model factorisations, and cus…☆41Updated 4 months ago
- A Fast sketching based solver for large scale ridge regression☆17Updated 8 months ago
- Functional models and algorithms for sparse signal processing☆89Updated last year
- PyProximal – Proximal Operators and Algorithms in Python☆58Updated this week
- Code for the Paper "Physics-Informed Gaussian Process Regression Generalizes Linear PDE Solvers"☆25Updated 10 months ago
- Proximal optimization in pure python☆116Updated 2 years ago
- Codes for Hilbert space reduced-rank GP regression☆14Updated 5 years ago
- Proximal algorithms and operators in python☆25Updated 5 years ago
- Code for the paper "XTrace: Making the most of every sample in stochastic trace estimation"☆12Updated last year
- Painless optimisation of constrained variables in AutoGrad, TensorFlow, PyTorch, and JAX☆23Updated 2 years ago
- A Julia implementation of sparse Gaussian processes via path-wise doubly stochastic variational inference.☆33Updated 4 years ago
- Implementation for Non-stationary Spectral Kernels (NIPS 2017)☆20Updated 5 years ago
- Light-weighted code for Orthogonal Additive Gaussian Processes☆41Updated 7 months ago