ComputingNotes

Federated Learning Algorithm Averaging Methods FedAvgM, FedProx, FedAvg

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FedAvg: https://arxiv.org/abs/1602.05629 __________________________________________________________________________________________________________ FedAvgM: https://arxiv.org/pdf/1909.06335 stands for Federated Averaging with Server Momentum. It is an upgrade to the original FedAvg algorithm designed specifically to solve the “Client Drift” problemwhere the model gets confused because different users have very different data (Non-IID). The Formula: How it works mathematically The FedAvgM update happens in three steps on ... Read More

Introduction to statistics

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Book: Statistics – An Introduction (4th Edition) – Roger E. Kirk What is statistics? Why statistics? Basic Concepts Terms: Types of Statistics: Descriptive and Inferential Random Sampling – draw sample from population; chance of drawing sample has equal chance Characteristics: Variable and Constant Measurment: Assign number to characteristics of people etc.

Deutsch’s Algorithm

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https://quantum.cloud.ibm.com/learning/en/courses/fundamentals-of-quantum-algorithms/quantum-query-algorithms/deutsch-algorithmhttps://en.wikipedia.org/wiki/Deutsch%E2%80%93Jozsa_algorithm Implementaion link: https://github.com/computingnotes/QuantumAlgorithmsUsingQiskit/blob/main/deutsch_algorithm_using_qiskit.ipynbGitHub: https://github.com/computingnotes deutsch_algorithm_using_qiskit (1) MathJax.Hub.Queue(["Typeset", MathJax.Hub]); } } init_mathjax(); mermaid.initialize({ maxTextSize: 100000, maxEdges: 100000, startOnLoad: false, fontFamily: window .getComputedStyle(document.body) .getPropertyValue("--jp-ui-font-family"), theme: document.querySelector("body[data-jp-theme-light='true']") ? "default" : "dark", }); let _nextMermaidId = 0; function makeMermaidImage(svg) { const img = document.createElement("img"); const doc = parser.parseFromString(svg, "image/svg+xml"); const svgEl = doc.querySelector("svg"); const { maxWidth } = ... Read More

Quantum Parallelism

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Quantum Computation and Quantum Information, Machael A. Nielsen, Isaac L. Chuang Quantum Parallelism is foundational technique that gives quantum computers their potential speed advantage. It explains how a quantum computer can evaluate a function f(x) for many different input values x simultaneously, a feat impossible for a classical computer. The oracle Uf​ maps the basis ... Read More

Deep Reinforcement Learning Parameters

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Epsilon (ϵepsilon 𝜖): This is a hyperparameter (a value between 0 and 1) that defines the probability of an agent taking a random action (exploration) instead of the action believed to have the highest reward (exploitation). Epsilon Decay: This is the process of gradually reducing the value of 𝜖 over time or a number of ... Read More

All Machine Learning MOdels

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https://www.ibm.com/think/topics/machine-learning-types Machine learning models are grouped in one of 5 types, supervised, unsupervised, self-supervised, semi-supervised and reinforcement learning. Machine learning libraries, useful.

Pilots and Least Squares work

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BPSK (Binary Phase Shift Keying), a fundamental digital modulation scheme. A receiver uses a simple technique called Least Squares (LS) Channel Estimation to defeat fading and multipath interference. Wireless Channel In this simulation, the channel is designed to be intentionally difficult. It includes two major issues of digital signals: The Transmission Strategy: The Pilot Block ... Read More

pskmod, awgn, rayleigh – matlab

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Notes from – pskmod: Modulate signal using M-PSK method https://au.mathworks.com/help/comm/ref/pskmod.html The pskmod function performs M-ary Phase Shift Keying (M-PSK) modulation, converting input symbols (X) into a complex baseband signal (Y). Key Syntax data = randi([0 M-1], 1000, 1); txSig = pskmod(data, M, pi/M); Adding fading to simulation models a more complex and realistic wireless channel ... Read More

Channel Estimation

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The goal is to solve for H (the Channel) in the equation: Y=H⋅X+N (Received Signal = Channel × Transmitted Signal + Noise) [1]W. Shen, “Deep Learning-Enabled Channel Estimation for Reconfigurable Intelligent Surfaces-Aided Wireless Communications”. 1. Pilot Insertion (The “Known” Data) The receiver cannot estimate the channel using random user data because it doesn’t know what ... Read More

MNIST PCA

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https://medium.com/@azimkhan8018/a-beginners-guide-to-deep-learning-with-mnist-dataset-0894f7183344https://ranasinghiitkgp.medium.com/principal-component-analysis-pca-with-code-on-mnist-dataset-da7de0d07c22https://github.com/mkosaka1/MNIST_PCA_CNN/blob/main/PCA%20%2B%20CNN.ipynbhttps://gist.github.com/tommct/1490cdf856d745ba41c1ac99ada2b579
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