Classifying the Blur and Clear Images
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Updated
Oct 3, 2023 - Python
Classifying the Blur and Clear Images
Pytorch implementation of preconditioned stochastic gradient descent (affine group preconditioner, low-rank approximation preconditioner and more)
Exploiting Explainable Metrics for Augmented SGD [CVPR2022]
Python implementation of stochastic sub-gradient descent algorithm for SVM from scratch
Tensorflow implementation of preconditioned stochastic gradient descent
Stochastic gradient descent with model building
[Python] [arXiv/cs] Paper "An Overview of Gradient Descent Optimization Algorithms" by Sebastian Ruder
Implement a Neural Network trained with back propagation in Python
SVM with Learning Using Privileged Information (LUPI) framework
ICLR 2021: Noise against noise: stochastic label noise helps combat inherent label noise
SC-Adagrad, SC-RMSProp and RMSProp algorithms for training deep networks proposed in
Implemenation of DDPG with numpy only (without Tensorflow)
PyDTNN - Python Distributed Training of Neural Networks
In this paper, we propose Filter Gradient Decent (FGD), an efficient stochastic optimization algorithm that makes a consistent estimation of the local gradient by solving an adaptive filtering problem with different designs of filters.
Black-box spike and slab variational inference, example with linear models
Parametric estimation of multivariate Hawkes processes with general kernels.
AdaHMG: A first-order stochastic optimization algorithm for time series data
This repository includes the scripts to replicate the results of my WORKING paper entitled "A Machine Learning Approach to Detect Accounting Frauds".
Byzantine Resilient Federated Learning
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