git-xp / Non-Convex-NewtonLinks
☆15Updated 7 years ago
Alternatives and similar repositories for Non-Convex-Newton
Users that are interested in Non-Convex-Newton are comparing it to the libraries listed below
Sorting:
- A suite of stochastic optimization methods for solving the empirical risk minimization problem.☆16Updated 5 years ago
- tensorflow implementation of the Wasserstein (aka optimal transport) distance☆72Updated 4 years ago
- Supporting code for "Parallel Streaming Wasserstein Barycenters"☆10Updated 7 years ago
- LIBS2ML: A Library for Scalable Second Order Machine Learning Algorithms☆12Updated 4 years ago
- Optimization using Stochastic quasi-Newton methods☆43Updated 8 years ago
- Riemannian stochastic optimization algorithms: Version 1.0.3☆64Updated 2 years ago
- Tensor Train decomposition on TensorFlow☆225Updated 4 years ago
- Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326☆71Updated 7 years ago
- Source code for "Sub-sampled Cubic Regularization for Non-convex Optimization", JM Kohler, A Lucchi, https://arxiv.org/abs/1705.05933☆16Updated 6 years ago
- Frank-Wolfe optimization variants with a linear convergence rate☆22Updated 9 years ago
- A variational inference method with accurate uncertainty estimation. It uses a new semi-implicit variational family built on neural netwo…☆54Updated 11 months ago
- Stochastic Optimization for Optimal Transport☆22Updated 8 years ago
- Adaptive gradient descent without descent☆48Updated 3 years ago
- AAAI & CVPR 2016: Preconditioned Stochastic Gradient Langevin Dynamics (pSGLD)☆35Updated 7 years ago
- Deep Kernel Learning. Gaussian Process Regression where the input is a neural network mapping of x that maximizes the marginal likelihood☆94Updated 7 years ago
- Sample implementations of proximal operators☆194Updated 12 years ago
- simple MATLAB code for randomized matrix computation☆23Updated 9 years ago
- Uncertainty Autoencoders, AISTATS 2019☆56Updated 6 years ago
- Lua implementation of Entropy-SGD☆82Updated 7 years ago
- Additive Gaussian Process Bandits - version 1.0☆27Updated 8 years ago
- hessian in pytorch☆187Updated 4 years ago
- ☆83Updated 5 years ago
- Deep neural network kernel for Gaussian process☆211Updated 5 years ago
- Code for the paper "Let’s Make Block Coordinate Descent Go Fast"☆48Updated 2 years ago
- A manifold optimization library for deep learning☆249Updated 4 years ago
- Gabriel Peyré, Marco Cuturi, Justin Solomon, Gromov-Wasserstein Averaging of Kernel and Distance Matrices, Proc. of ICML 2016.☆74Updated 9 years ago
- matlab code for convex optimization based tensor decomposition (completion/denoising)☆44Updated 10 years ago
- Wasserstein / earth mover's distance visualizations☆66Updated 8 years ago
- A tutorial on "Bayesian Compression for Deep Learning" published at NIPS (2017).☆206Updated 6 years ago
- Optimization with orthogonal constraints and on general manifolds☆130Updated 5 years ago