Exercise 1. Computational Finance with C++ Coursework Due: 5/06/2019 The aim of this exercise is to construct a portfolio optimization solver and perform backtesting to assess the performance the Markowitz model. You are given a file containing returns from 83 of the FTSE 100 companies. The data is contained in a file called “assets_returns.csv”. You […]
代写 C++ algorithm software Exercise 1. Read More »
Department of Computer Science and Software Engineering SEMESTER 1, 2018 EXAMINATIONS CITS1001 Object-oriented Programing and Software Engineering FAMILY NAME: ____________________________ GIVEN NAMES: ______________________ STUDENT ID: SIGNATURE: ___________________________ This Paper Contains: 20 pages (including title page) Time allowed: 2:00 hours INSTRUCTIONS: Answer all questions. The paper contains eight questions, each worth ten marks. Write
Project 2, TCSS 380 Spring 2019 OBJECTIVE The objective of this project is to apply your newly learned Erlang knowledge to solve an interesting puzzle. ASSIGNMENT DESCRIPTION For this assignment, you are to write a program that finds a circular train constructed from all domino tiles from the given set of dominoes using a list
代写 R data structure algorithm game graph Project 2, TCSS 380 Spring 2019 Read More »
4274 IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, VOL. 56, NO. 8, AUGUST 2018 Missing Data Reconstruction in Remote Sensing Image With a Unified Spatial–Temporal–Spectral Deep Convolutional Neural Network Qiang Zhang , Student Member, IEEE, Qiangqiang Yuan , Member, IEEE, Chao Zeng, Xinghua Li , Member, IEEE, and Yancong Wei, Student Member, IEEE Abstract—Because of
代写 algorithm deep learning html parallel graph statistic network theory 4274 Read More »
DLP project pg. 1 DATA LEVEL PARALLELISM 05/24/19 DLP Project (DUE: Friday. 6/7/2019, 11:59PM Learn the data-parallel programming paradigm and become familiar with CUDA by implementing an algorithm on the GPU. DLP project pg. 2 Data Level Parallelism BACKGROUND In this project, you will do template matching on a GPU. Template matching is used to
代写 algorithm html parallel cuda GPU DLP project Read More »
• skip to content  cmps11s19 User Tools • Logged in as: Ziran Zhao (Darren) (zzhao102) • Update Profile • Log Out Site Tools Search ToolsShow pagesourceOld revisionsBacklinksMedia ManagerSitemapUpdate ProfileLog Out • Media Manager • Sitemap You are here: Welcome to cmps11s19 » Assignments for cmps11s19 » Assignment 08: AI Battleship Player assignments:assignment_08 −Table of
代写 algorithm game GUI Java math AI operating system statistic • skip to content Read More »
CMPS 102 Practice Midterm 3 June 01, 2017 Quiz 3 on June 07, 2019; counts like the other midterms. 1 Estimating Sums, Recurrences (Big Θ) Mainly, similar in format to midterms 1 and 2. The Master Theorem will be stated, as it has been. MASTER THEOREM, ETC. — OK TO TEAR THIS PAGE OFF. As
Homework 7.1: Digital Image Processing Author: Qifan Zhang Get Started To get started, please simply fork this GitLab repository and follow the structure and submissions guidelines below. Remember to change your repo to a private one before you commit to it. Kind Reminder: The following tasks are arranged from easy to hard. Arrange your coding
代写 data structure algorithm python Homework 7.1: Digital Image Processing Read More »
MODULAR PROGRAMME COURSEWORK ASSESSMENT SPECIFICATION Module Details Module Code UFCFT4-15-3 Run sem 3 FIRST SIT 2018/19 Module Title Cryptography Module Leader Emily Chui Module Tutors Emily Chui Component and Element Number Program (including source code and executable) and Individual Report Weighting: (% of the Module’s assessment) 75% Element Description Implementation of what have learnt in
School of Computer Science The University of Adelaide Artificial Intelligence Assignment 3 Semester 1, 2019 Probabilistic graphical models Your task is to perform inference on a probabilistic graphical model (PGM) of boolean (i.e. true/false) random variables. There are two options available for this assignment, either: Option 1 Implement code in Java/C/C++/Python to perform approximate inference