Lecture Note 05 EECS 4101/5101 Instructor: Andy Mirzaian SKEW HEAPS: Self-Adjusting Heaps In this handout we describe the skew heap data structure, a self-adjusting form of heap related to the leftist heap of Crane and Knuth. Skew heaps, in contrast to leftist heaps, use less space and are easier to implement, and yet in the […]
CSCI 570 – Spring 2021 – HW 3 Rubric 1 Solve the following recurrences by giving tight Θ-notation bounds in terms of n for sufficiently large n. Assume that T(·) represents the running time of an algorithm, i.e. T(n) is positive and non-decreasing function of n and for small constants c independent of n, T(c)
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3-opt COMP5329 – Deep Learning¶ Tutorial 3 – Optimization¶ Semester 1, 2021 Objectives: To learn about gradient descent optimization. To understand the algorithm of Momentum. To understand the algorithm of AdaGrad. To understand the algorithm of Adam. (Exercise) Instructions: For more details about AdaGrad or Adam, please refer to Chapter 8 of Goodfellow, I., Bengio,
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CSCI 576 Assignment 3 Instructor: Parag Havaldar Assigned on 03/15/2021 Solutions due 03/31/2021 before 10 am, morning THEORY QUESTIONS – (40 points) Question 1: DCT Coding (15 points) In this question you will try to understand the working of DCT in the context of JPEG. Below is an 8×8 luminance block of pixel values and
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Lecture 5. FuncLang – Functions February 23, 2021 Overview FuncLang: writing programs in functional programming languages lambda expression recursion high-order functions build-in functions (list, pair) control structures Syntax Semantics Implementation Abstraction in Programming Languages Variable in imperative programming languages fixed abstraction – you cannot
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Lecture Note 04 EECS 4101/5101 Instructor: Andy Mirzaian LEFTIST HEAPS Leftist heaps are a data structure for representing priority queues. They were discovered by Clark A. Crane [1971] (also described in Knuth, Art of Computer Programming, vol. 3, 1973, pp. 151-152) and have the following nice properties: • INSERT and DELETEMIN operations can be performed
2-MLP COMP5329 – Deep Learning¶ Tutorial 2 – Multilayer Neural Network¶ Semester 1, 2021 Objectives: To understand the multi-layer perceptron. To become familiar with backpropagation. Instructions: Go to File->Open. Drag and drop “lab2MLP_student.ipynb” file to the home interface and click upload. Read the code and complete the exercises. To run the cell you can press
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PowerPoint Presentation EECS 4101/5101 B-trees 2-3-4 trees Prof. Andy Mirzaian Lists Move-to-Front Search Trees Binary Search Trees Multi-Way Search Trees B-trees Splay Trees 2-3-4 Trees Red-Black Trees SELF ADJUSTING WORST-CASE EFFICIENT competitive competitive? Linear Lists Multi-Lists Hash Tables DICTIONARIES 2 References: [CLRS] chapter 18 3 B-trees R. Bayer, E.M. McCreight, “Organization and maintenance of large
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Chapter 4 Definelang: A Language with Global Variables Our goal in this chapter is to learn about global definitions and usage, and to contrast them with locally scoped definitions discussed in the previous chapter. 4.1 Local vs. Global Definitions So far each variable that we have defined in a let expression has had a local
CSCI 570 – Spring 2021 – HW 4 Due April 01, by 4AM PST Note. You are to solve problems 2, 3 and 4 by using the following steps: 1. Describe how to construct a flow network. 2. Make a claim. Something like ”this problem has a feasible solution if and only if the max
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