Lecture Note 01 EECS 4101/5101 Instructor: Andy Mirzaian AMORTIZATION and SELF-ADJUSTMENT In the recent years a powerful technique in the complexity analysis of data structures called “amortization” , or averaging over time, has emerged. Amortized running time is a realistic but robust complexity measure for which we can obtain surprisingly tight upper and lower bounds […]
Lecture Note 03 EECS 4101/5101 Instructor: Andy Mirzaian SPLAY TREES: Self-Adjusting Binary Search Trees In 1983, D.D. Sleator and R.E. Tarjan invented an interesting data structure for implement- ing the dictionary abstract data type, called a splay tree, a self-adjusting version of binary search trees. A self-adjusting BST is a BST maintained in a particular
2-MLP-checkpoint 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 Search 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 TOPICS Binary Trees Binary Search Trees Multi-way Search Trees 3 References: [CLRS] chapter 12 4 Binary
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Lecture Note 02 EECS 4101/5101 Instructor: Andy Mirzaian SELF-ADJUSTING LINEAR LISTS Analysis of the “Move to Front” Heuristic The problem we shall study here (see [3]) is often called the dictionary problem: Maintain a set of items under an intermixed sequence of the following kinds of opera- tions: access(x): insert(x): delete(x): Locate item x in
Lecture Note 06 EECS 4101/5101 Instructor: Andy Mirzaian ANALYSIS OF THE UNION-FIND ALGORITHM In this handout we are going to analyze the worst case time complexity of the UNION-FIND algorithm that uses a forest of ‘‘up trees’’ (i.e. trees where each node has only a pointer to its par- ent) with weight (or size) balancing
Accurate and Efficient Modeling of 802.15.4 Unslotted CSMA/CA through Event Chains Computation Domenico De Guglielmo, Francesco Restuccia, Giuseppe Anastasi, Marco Conti, and Sajal K. Das Abstract—Many analytical models have been proposed for evaluating the performance of event-driven 802.15.4 Wireless Sensor Networks (WSNs), in Non-Beacon Enabled (NBE) mode. However, existing models do not provide accurate analysis
PowerPoint Presentation EECS 4101/5101 Priority Queues Prof. Andy Mirzaian TOPICS Priority Queues Leftist Heaps Skew Heaps Binomial Heaps Fibonacci Heaps Recent Developments 2 References: [CLRS 2nd edition] chapters 19, 20 or [CLRS 3rd edition] chapter 19 & Problem 19-2 (pp:527-529) Lecture Notes 4, 5 AAW animations 3 Priority Queues 4 Basic Priority Queues Each item
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PowerPoint Presentation EECS 4101/5101 Move to Front Self Adjusting Linear Lists 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 TOPICS in this slide Linear List with Move-to-Front Competitiveness of Move-to-Front:
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Matrix Multiplication and Cache Friendly Code COMP 273 Winter 2021 – Assignment 4, Prof. Kry Available: 24 March – Due date: 12 April 1 Introduction In this assignment you will write code to multiply two square n × n matrices of single precision floating point numbers, and then optimize the code to exploit a memory