PyHessian is a Pytorch library for second-order based analysis and training of Neural Networks
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Apr 16, 2024 - Jupyter Notebook
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second-order-optimization
Here are 43 public repositories matching this topic...
ADAHESSIAN: An Adaptive Second Order Optimizer for Machine Learning
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Feb 27, 2023 - Python
A C++ interface to formulate and solve linear, quadratic and second order cone problems.
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Jul 30, 2021 - C++
Pytorch implementation of preconditioned stochastic gradient descent (Kron and affine preconditioner, low-rank approximation preconditioner and more)
deep-learning pytorch lie-groups optimization-algorithms stochastic-gradient-descent preconditioner low-rank-approximation kronecker-factored-approximation second-order-optimization affine-group hessian-vector-product
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Dec 14, 2024 - Python
Distributed K-FAC Preconditioner for PyTorch
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Dec 25, 2024 - Python
FEDL-Federated Learning algorithm using TensorFlow (Transaction on Networking 2021)
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Nov 29, 2020 - Python
This repository implements FEDL using pytorch
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Nov 6, 2020 - Python
Tensorflow implementation of preconditioned stochastic gradient descent
deep-learning tensorflow lie-groups optimization-algorithms stochastic-gradient-descent preconditioner low-rank-approximation second-order-optimization affine-group hessian-vector-product
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Nov 23, 2023 - Python
PyTorch implementation of the Hessian-free optimizer
deep-neural-networks deep-learning conjugate-gradient optimization-algorithms stochastic-optimizers newtons-method matrix-free second-order-optimization hessian-free pytorch-implementation ggn
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Jun 14, 2024 - Python
Hessian-based stochastic optimization in TensorFlow and keras
tensorflow optimization keras optimization-algorithms stochastic-optimization newton-method second-order-optimization
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Mar 29, 2022 - Python
Compatible Intrinsic Triangulations (SIGGRAPH 2022)
computer-graphics bijection geometry-processing siggraph parameterization bijective-maps triangle-mesh second-order-optimization siggraph2022 cross-parameterization inter-surface-mapping intrinsic-triangulation compatible-triangulation
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Jun 7, 2022 - C++
This package is dedicated to high-order optimization methods. All the methods can be used similarly to standard PyTorch optimizers.
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Nov 28, 2024 - Python
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Mar 1, 2022 - Jupyter Notebook
Implementation of PSGD optimizer in JAX
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Dec 8, 2024 - Python
An implementation of PSGD Kron second-order optimizer for PyTorch
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Dec 2, 2024 - Python
Federated Learning using PyTorch. Second-Order for Federated Learning. (IEEE Transactions on Parallel and Distributed Systems 2022)
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Jun 10, 2022 - Jupyter Notebook
Minimalist deep learning library with first and second-order optimization algorithms made for educational purpose
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Aug 1, 2023 - Python
LIBS2ML: A Library for Scalable Second Order Machine Learning Algorithms
c-plus-plus big-data matlab machine-learning-algorithms stochastic octave-scripts mex-files large-scale-learning matlab-script stochastic-optimization second-order-optimization
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Sep 14, 2021 - C++
Prototyping of matrix free Newton methods in Julia
optimization julia optimization-algorithms stochastic-optimization newton-method second-order-optimization
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Aug 17, 2021 - Julia
Subsampled Riemannian trust-region (RTR) algorithms
big-data optimization optimization-algorithms gradient-descent-algorithm stochastic-optimizers stochastic-gradient-descent sampling-methods subsample large-scale-optimizations riemannian-geometry riemannian-manifold trust-region sub-sampling second-order-optimization riemannian-optimization
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Jan 5, 2023 - MATLAB
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