Gaussian Mixture Model with low rank approximation
-
Updated
Jun 2, 2020 - Python
Gaussian Mixture Model with low rank approximation
Proyecto para el Trabajo Final de Grado: Aplicación de técnicas de inteligencia artificial para la generación automática de escenarios a partir de lenguaje natural.
IE 531 - Algorithms for Data Analytics. A detailed description of each assignment is provided.
This repository is the official code for the paper "Enhanced MRI Brain Tumor Detection and Classification via Topological Data Analysis and Low-Rank Tensor Decomposition" by Serena Grazia De Benedictis, Grazia Gargano and Gaetano Settembre.
Numerical experiments for Optima-TT method from teneva python package. This method finds items which relate to min and max elements of the tensor in the tensor train (TT) format.
Linear Algebra project `Decomposition into Low-Rank and Sparse Matrices in Computer Vision` | Applied Sciences Faculty, UCU (2019)
Deep learning models have become state of the art for natural language processing (NLP) tasks, however deploying these models in production system poses significant memory constraints. Existing compression methods are either lossy or introduce significant latency. We propose a compression method that leverages low rank matrix factorization durin…
The repository contains code to reproduce the experiments from our paper Error Feedback Can Accurately Compress Preconditioners available below:
Lowrankdensity
MUSCO: Multi-Stage COmpression of neural networks
My experiment of multilayer NMF, a deep neural network in which the first several layers take Semi-NMF as its pseudo-activation-function that finds the latent sturcture embedding in the original data unsupervisely.
Solver in the low-rank tensor train format with cross approximation approach for the multidimensional Fokker-Planck equation
Pytorch implemenation of "Learning Filter Basis for Convolutional Neural Network Compression" ICCV2019
[ICLR 2022] Code for paper "Exploring Extreme Parameter Compression for Pre-trained Language Models"(https://arxiv.org/abs/2205.10036)
GaLore: Memory-Efficient LLM Training by Gradient Low-Rank Projection
Tensorflow implementation of preconditioned stochastic gradient descent
A framework based on the tensor train decomposition for working with multivariate functions and multidimensional arrays
Group Sparsity: The Hinge Between Filter Pruning and Decomposition for Network Compression. CVPR2020.
VIP is a python package/library for angular, reference star and spectral differential imaging for exoplanet/disk detection through high-contrast imaging.
LoRA (Low-Rank Adaptation) inspector for Stable Diffusion
Add a description, image, and links to the low-rank-approximation topic page so that developers can more easily learn about it.
To associate your repository with the low-rank-approximation topic, visit your repo's landing page and select "manage topics."