• Connected Components of Chaos

  • Auteur(s): AmCan Tech
  • Podcast

Connected Components of Chaos

Auteur(s): AmCan Tech
  • Résumé

  • A podcast where logic meets lunacy, and graphs guide the way through the madness! Join us as we explore the beautiful intersections of mathematical logic, graph theory, discrete math, computer science, and the quirky chaos of everyday life. From proving theorems to untangling graph traversals, we’ll connect seemingly random dots to create a web of ideas that’s as entertaining as it is enlightening.

    AmCan Tech
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Épisodes
  • QuickSort and Order Selection
    Dec 20 2024
    This episode focuses on QuickSort, a divide-and-conquer sorting algorithm, comparing it to MergeSort, and analyzing its average and worst-case time complexities. It then explains the order selection problem, which involves finding the kth smallest element in a dataset, presenting several algorithms with varying time complexities and practical considerations, including a linear worst-case algorithm and an approximate heuristic. The analysis includes recurrence relations and their solutions to determine the algorithm's efficiency. Finally, it contrasts the different approaches for solving the order selection problem based on their performance characteristics.








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    14 min
  • Recurrence Equations and Asymptotic Notation
    Dec 15 2024
    This episodes presents methods for solving recurrence equations, which are crucial for analyzing the time complexity of recursive algorithms. It introduces asymptotic notations (Big O, Big Omega, Big Theta, little o, little omega) to describe the growth of functions. The lecture then explores several techniques for solving recurrences, including the substitution method, iteration method (and recursion trees), the Master Theorem, and solving homogeneous and non-homogeneous linear recurrences. Specific examples such as merge sort, binary search, and the Towers of Hanoi are used to illustrate these techniques. Finally, the limitations of the Master Theorem are discussed, along with strategies for handling cases where it is not applicable.








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    20 min
  • Physics and Computer Science
    Nov 30 2024
    The 2024 Nobel Prize in Physics was awarded to John Hopfield and Geoffrey Hinton for their foundational work on artificial neural networks (ANNs). The award citation highlights their contributions to machine learning, linking ANNs to concepts in physics, such as spin models and statistical mechanics. Hopfield's research focused on recurrent networks and their applications in associative memory and optimization, while Hinton's work involved stochastic models like the Boltzmann machine and advancements in deep learning techniques. Their combined efforts revolutionized the field, leading to widespread applications across various scientific disciplines and everyday technologies.
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    13 min

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