facebookresearch / RidgeSketch
A Fast sketching based solver for large scale ridge regression
☆17Updated 8 months ago
Alternatives and similar repositories for RidgeSketch:
Users that are interested in RidgeSketch are comparing it to the libraries listed below
- Solves the best subset selection problem☆41Updated 3 years ago
- "Discontinuous Hamiltonian Monte Carlo for sampling discrete parameters" by Akihiko Nishimura, David Dunson, Jianfeng Lu☆27Updated 6 years ago
- Fast hyperparameter settings for non-smooth estimators:☆39Updated last year
- Unbiased Markov chain Monte Carlo with couplings☆29Updated 2 years ago
- "Variational inference tools to leverage estimator sensitivity."☆16Updated last year
- Practical tools for quantifying how well a sample approximates a target distribution☆27Updated 4 years ago
- Efficient Algorithms for L0 Regularized Learning☆97Updated last year
- Efficient, lightweight variational inference and approximation bounds☆43Updated last year
- Code for the paper "Randomly pivoted Cholesky: Practical approximation of a kernel matrix with few entry evaluations"☆28Updated 4 months ago
- A Julia implementation of sparse Gaussian processes via path-wise doubly stochastic variational inference.☆33Updated 4 years ago
- Lightweight library of stochastic gradient MCMC algorithms written in JAX.☆100Updated last year
- Learning with operator-valued kernels☆22Updated 2 years ago
- An ultra-lightweight JAX implementation of sparse Gaussian processes via pathwise sampling.☆22Updated 3 years ago
- A simple library to run variational inference on Stan models.☆30Updated last year
- ☆13Updated this week
- A suite of stochastic optimization methods for solving the empirical risk minimization problem.☆16Updated 5 years ago
- This code is no longer maintained. The codebase has been moved to https://github.com/scikit-learn-contrib/skglm. This repository only ser…☆17Updated 2 years ago
- Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods☆17Updated 3 years ago
- Tools for JAX☆44Updated this week
- Skew Gaussian Processes by Alessio Benavoli, Dario Azzimonti and Dario Piga☆13Updated 3 years ago
- FALKON implementation used in the experimental section of "FALKON: An Optimal Large Scale Kernel Method"☆29Updated 4 years ago
- Riemannian Optimization Using JAX☆48Updated last year
- Exponential families for JAX☆63Updated this week
- ☆12Updated 3 years ago
- some scripts for the couplings enthusiasts!☆32Updated 4 years ago
- Tutorials and sampling algorithm comparisons☆70Updated this week
- This tutorial is a basic guide to understanding the Zig-Zag Sampling method. This document is released with the aim of diffusion and shar…☆19Updated 5 years ago
- CHOP: An optimization library based on PyTorch, with applications to adversarial examples and structured neural network training.☆77Updated 11 months ago
- Quantifying and reporting uncertainty in drug discovery predictions with probabilistic models☆11Updated 2 years ago
- Code for the paper "XTrace: Making the most of every sample in stochastic trace estimation"☆12Updated last year