Caffe for Sparse and Low-rank Deep Neural Networks

Python machine learning applications in image processing, recommender system, matrix completion, netflix problem and algorithm implementations including Co-clustering, Funk SVD, SVD++, Non-negative Matrix Factorization, Koren Neighborhood Model, Koren Integrated Model, Dawid-Skene, Platt-Burges, Expectation Maximization, Factor Analysis, ISTA, FISTA, ADMM, Gaussian Mixture Model, OPTICS, DBSCAN, Random Forest, Decision Tree, Support Vector Machine, Independent Component Analysis, Latent Semantic Indexing, Principal Component Analysis, Singular Value Decomposition, K Nearest Neighbors, K Means, Naïve Bayes Mixture Model, Gaussian Discriminant Analysis, Newton Method, Coordinate Descent, Gradient Descent, Elastic Net Regression, Ridge Regression, Lasso Regression, Least Squares, Logistic Regression, Linear Regression

Pytorch implementation of preconditioned stochastic gradient descent (Kron and affine preconditioner, low-rank approximation preconditioner and more)

Multi-channel Weighted Nuclear Norm Minimization for Real Color Image Denoising, ICCV 2017.

LoRA (Low-Rank Adaptation) inspector for Stable Diffusion

Fine-tuning of diffusion models

VIP is a python package/library for angular, reference star and spectral differential imaging for exoplanet/disk detection through high-contrast imaging.

Group Sparsity: The Hinge Between Filter Pruning and Decomposition for Network Compression. CVPR2020.

A framework based on the tensor train decomposition for working with multivariate functions and multidimensional arrays

Pytorch implementation of Factorizer.

Tensorflow implementation of preconditioned stochastic gradient descent

HiCMA: Hierarchical Computations on Manycore Architectures

[ICLRW'26] EoRA: Fine-tuning-free Compensation for Compressed LLM with Eigenspace Low-Rank Approximation

GaLore: Memory-Efficient LLM Training by Gradient Low-Rank Projection

[ICLR 2022] Code for paper "Exploring Extreme Parameter Compression for Pre-trained Language Models"(https://arxiv.org/abs/2205.10036)

A family of highly efficient, lightweight yet powerful optimizers.

Pytorch implemenation of "Learning Filter Basis for Convolutional Neural Network Compression" ICCV2019

Methods for label-free mass spectrometry proteomics

PyTorch implementation of quantization-aware matrix factorization (QMF) for data compression

Solver in the low-rank tensor train format with cross approximation approach for the multidimensional Fokker-Planck equation

Python Library for running SHARE (Compress multiple LoRA adapters into a shared subspace)

Multi-slice MR Reconstruction with Low-Rank Tensor Completion

Convolutive Matrix Factorization in Julia

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.

Dense Matrix Market

Deformable Groupwise Image Registration using Low-Rank and Sparse Decomposition

MUSCO: Multi-Stage COmpression of neural networks

This repository contains MATLAB files for the implementation of work proposed in the paper Efficient Structure-preserving Support Tensor Train Machine.

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.

Software for Testing Accuracy, Reliability and Scalability of Hierarchical computations.