ComputingNotes

LM, N-Grams, RNNs, LLM, Fine Tuning, LoRA, QLoRA – Part I

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Introduction to Large Language Modelshttps://developers.google.com/machine-learning/crash-course/llm What is Language Model? At its simplest, a language model is a statistical tool that predicts the next piece of text in a sequence. The N-gram Approach Early language models used “N-grams,” which are simply ordered sequences of words where N represents the number of words. Context Context refers to ... Read More

Quantum Error Correction Challenges – Quantum Computing

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Books References: Exploration in Quantum Computing by Colin P. WilliamsQuantum Computation and Quantum Information by Nielsen et. al Quantum error correction (QEC) is widely considered the “holy grail” of quantum computing and also its most formidable bottleneck. While classical computers can easily correct errors by copying data (redundancy), quantum computers are forbidden from doing this ... Read More

Data Structure and Algorithms – An Overview

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T. H. Cormen, Ed., Introduction to algorithms, 2nd. ed., 10th pr. Cambridge, Mass.: MIT Press [u.a.], 2007. Data Structure and Algorithsm, Sixth Edition, GoodRich et al., Wiley What is a data structure? https://www.ibm.com/think/topics/data-structure What are algorithms? An Algorithm is simply a specific, step-by-step set of instructions used to complete a task or solve a problem. ... Read More

Calculus – Application of Integrals (Area between Curves)

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References: Integrals can be used to calculate many things such as area between curves, volumes and surfaces of solids, length of curves etc. Areas between Curves: In calculus, we define the exact area under a curve not by measuring it directly, but by slicing it into rectangles, adding them up, and then making the slices ... Read More

Quantum Error Correction – Quantum Computing

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Books References: In an idea set up, we assume that logical qubits evolves unitarily following Schrodinger’s equation from the moment quantum comptuer is prepared, go through some computations and measured. However, during this process, real quantum system couples with its environment causing information leak out of logical state of the qubits in the quantum memory ... Read More

Random Linear Network Coding (RLNC)

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Network Coding Approaches for Distributed Computation over Lossy Wireless Networks https://pmc.ncbi.nlm.nih.gov/articles/PMC10047255B. Fan, B. Tang, Z. Qu, and B. Ye, “Network Coding Approaches for Distributed Computation over Lossy Wireless Networks,” Entropy, vol. 25, no. 3, p. 428, Feb. 2023, doi: 10.3390/e25030428. Ho, T.; Médard, M.; Koetter, R.; Karger, D.R.; Effros, M.; Shi, J.; Leong, B. A ... Read More

Network Coding – Wireless Communication

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https://www.nature.com/research-intelligence/nri-topic-summaries/network-coding-in-wireless-communication-systems-micro-22183https://www.microsoft.com/en-us/research/wp-content/uploads/2007/07/tr-2007-90.pdf Network Coding: Generalization of Routing Information delivery in today’s wireless networks is performed by routing which is intermediate nodes (routers) store and forward data. Now, network coding is the recent generalization of routing in which nodes can generate output data which is produced from encoding or applying certain functions on the previously received input ... Read More

Covert Communication (Low Probability of Detection – LPD)

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I. Makhdoom, M. Abolhasan, and J. Lipman, “A comprehensive survey of covert communication techniques, limitations and future challenges,” Computers & Security, vol. 120, p. 102784, Sep. 2022, doi: 10.1016/j.cose.2022.102784. Best Readings in Covert Communication and Networkinghttps://www.comsoc.org/publications/best-readings/covert-communication-and-networking Covert communication (often called LPD or Low Probability of Detection) is a security paradigm where the goal is not ... Read More

Probability – Introduction

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Book Probability by Jim Pitman, Springer The main concepts of probability theory include: These three concepts form the fundamental framework of probability theory. They describe the structure of any random process, from a simple coin toss to complex risk modeling. Outcome Space (Sample Space) The outcome space (often denoted by the Greek letter Omega, Ω, ... Read More

Linear Algebra – Gaussian Elimination

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Book: Introduction to Linear Algebra, Johnson et al. Third Edition Gaussian Elimination is a method in linear algebra used to solve systems of linear equations.It systematically transforms a system of equations into a simpler form so the solutions become easy to find. It works by manipulating the augmented matrix of the system using basic row ... Read More
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