Name: Saeed Damadi
Type: User
Company: University of Maryland, Baltimore County
Bio: I am pursuing two PhD's simultaneously in applied mathematics and electrical engineering at UMBC. My research is compression of deep neural networks.
Twitter: saeeddamadi
Location: Maryland, USA
Blog: https://sdamadi.github.io/
Saeed Damadi's Projects
This file is a final version of Composite Objective Mirror Descent method replicating Ketatos's paper
A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.
Comprehensive image classification for training multilayer perceptron (MLP), LeNet, LeNet5, conv2, conv4, conv6, VGG11, VGG13, VGG16, VGG19 with batch normalization, ResNet18, ResNet34, ResNet50, MobilNetV2 on MNIST, CIFAR10, CIFAR100, and ImageNet1K.
an implementation of L0 regularization with PyTorch
Introduction to linear algebra
Full reference of LinkedIn answers 2022 for skill assessments (aws-lambda, rest-api, javascript, react, git, html, jquery, mongodb, java, Go, python, machine-learning, power-point) linkedin excel test lösungen, linkedin machine learning test LinkedIn test questions and answers
PyTorch implementation of The Lottery Tickets Hypothesis.
A reimplementation of "The Lottery Ticket Hypothesis" (Frankle and Carbin) on MNIST.
This repository contains a Pytorch implementation of the paper "The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks" by Jonathan Frankle and Michael Carbin that can be easily adapted to any model/dataset.
Collection of scripts and tools related to machine learning
This folder contains OMD for voltage stability
Visual tracking library based on PyTorch.
Sparse models that have been obtained from pruning processes and quantization
Sparse Solution of Underdetermined Linear Equations by Stagewise Orthogonal Matching Pursuit
A python script that estimates the support and resistance lines of a stock's prices or a period
In this file I am going to write all useful codes that I have learned during my coding. Having them helps me to fresh my memory by looking at them quickly.