ComputingNotes

DRL Toolbox Matlab

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“Reinforcement Learning Toolbox,” Mathworks.com, 2026. https://au.mathworks.com/products/reinforcement-learning.html?requestedDomain= (accessed Feb 23, 2026). Implementing Deep Reinforcement Learning Toolbox Defining Observation and Action Spaces The first stage of development involves establishing the operational boundaries. Data specifications must be defined for both observations (system states) and actions (available commands). rlNumericSpec([5 1]); % Define continuous state space rlFiniteSetSpec(1:4); % Define discrete action ... Read More

Deep Reinforcement Learning

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Resources: 🛒 The Supermarket Analogy [Plaat et al. Page 25] Imagine you have just moved to a new city, you are hungry, and you want to buy some groceries. There is an unrealistic catch: you have no map and no smartphone. After some random exploration, you find a supermarket. You carefully note the route in ... Read More

Time Complexity – Computer Science

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Complexity Hierarchy Logarithmic: $O(\log n)$ The “Sublinear” breakthrough. Allows processing of massive matrices by only sampling specific parts. Linear: $O(n)$ The “Old” Standard. Required reading the entire input, which is impossible for modern recommendation scales. Polynomial: $O(poly(k))$ The “Classical Analogue.” While slower than quantum, it remains fast enough to be practical. Exponential: $O(2^n)$ The “Quantum ... Read More

Systems of Linear Equations and Matrices

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References: Linear Equation: At its simplest, a linear equation is an algebraic equation that creates a straight line when plotted on a graph. Every variable in the equation is raised to the first power (meaning no exponents like $x^2$ or $y^3$), and there are no variables multiplied by each other. The Standard Forms Depending on ... Read More

Machine Learning Applications – Learning Associations

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References: Learning Associations Association Rule Learning is a rule-based method used to discover interesting relations or “hidden patterns” between variables in large databases. It is primarily an unsupervised learning technique because it doesn’t require pre-labeled data; it simply looks for items that frequently occur together. The most famous application is Market Basket Analysis, which retailers ... Read More

Algorithm Analysis

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Resources: What is Algorithm? Asymptotic Notation In computer science, Asymptotic Notation is a mathematical language used to describe the efficiency of an algorithm as the input size (usually called $n$) grows toward infinity. It allows us to ignore hardware-specific details (like processor speed) and focus purely on how the time or space requirements of a ... Read More

Quantum Federated Learning with Qiskit

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Resources: What is Quantum Federated Learning? Quantum Federated Learning (QFL) is a decentralized machine learning framework where multiple clients collaboratively train a global quantum model without sharing their private, local data. In this framework, clients perform local training on their own datasets and then share only their updated model weights with a central server for ... Read More

Qiskit Machine Learning

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Resources: What is Qiskit Machine Learning? Qiskit Machine Learning is an open-source library built on top of the core Qiskit framework that integrates quantum computing with classical machine learning. It acts as a bridge, allowing researchers and developers to use quantum algorithms for tasks like classification, regression, and clustering. Instead of manually building every gate, ... Read More

Data Structure and Algorithms – Queues

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Resources: Queues are one of the most intuitive and widely used data structures in computer science. If you’ve ever waited in line at a coffee shop, ticket counter, or printer, you’ve already experienced a queue in real life! What is a Queue? A queue is an abstract data type that follows the FIFO principle – ... Read More
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