Algorithm 算法代写

算法代写代考包括以下内容:

  1. 概念:时间复杂度、空间复杂度、算法分析、数据结构代写
  2. 搜索算法:二叉搜索树、哈希表
  3. 排序算法:快速排序、归并排序
  4. 动态规划算法代写
  5. 图论:最短路径算法代写
  6. 数学:数论代写
  7. 代码实现:C / C++ / Java / Python代写

Algorithms courses typically include topics such as data structures, basic algorithms, graph algorithms, dynamic programming, computational geometry, and number theory. They can also include more advanced topics such as parallel algorithms, randomized algorithms, and approximation algorithms.

Spark LSH Big Data Assignment 3

1. Overview of the Assignment Assignment 3 In Assignment 3, you will complete two tasks. The goal is to familiarize you with Locality Sensitive Hashing (LSH), and different types of collaborative-filtering recommendation systems. The dataset you are going to use is a subset from the Yelp dataset used in the previous assignments. 2. Assignment Requirements …

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CS 434 MP2

ECE/CS 434 MP2 Due on Monday Feb 27 11:59PM on Gradescope Objective¶ In this MP, you will: Implement DUET algorithm to separate a mixture of N voice signals from received from two microphones Problem Overview¶ Consider a problem of separating N sources ($S_1$, $S_2$, … $S_N$) from recordings on 2 microphones ($R_1$ and $R_2$). According …

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COMP 3007 W22 Assignment 4

COMP 3007 A/B (Winter 2023) − “Programming Paradigms” Specification for Assignment 4 Your submission for this assignment must be commented and must include both your name and your student number as a comment at the top of every source file you submit. Each of your submitted files must use a file name beginning ‘comp3007_w23_#########_assignment_04’ (replacing …

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COMP3121 9101 23T1 — Assignment 1 (UNSW Sydney)

COMP3121/9101 23T1 — Assignment 1 (UNSW Sydney) Due Friday 3rd March at 5pm Sydney time In this assignment we review some basic algorithms and data structures, and we apply the divide- and-conquer paradigm. There are three problems each worth 20 marks, for a total of 60 marks. Partial credit will be awarded for progress towards …

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CS6601 AI Midterm Topics List

CS 6601: Midterm study guide R&N = AI, A Modern Approach , by Russell & Norvig ¡ñ Adversarial search (R&N Chapter 5) ¡ð Observable games (e.g. isolation) ¡ð Minimax ¡ð Alpha-beta pruning ¡ö Performance improvement ¡ð Utility and evaluation functions ¡ö Sensitivity ¡ð Optimization tricks ¡ö Move-ordering ¡ö Symmetry ¡ð Iterative deepening ¡ð Multiplayer games …

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CUDA MatrixMult

CUDA MatrixMult Design and implement C and CUDA programs that called MatrixMult.c, MatrixMultNaive.cu, and MatrixMultTiled.cu. The MatrixMult.c, MatrixMultNaive.cu, and MatrixMultTiled.cu programs will use a command line argument that corresponds to the row/column length to multiply two square matrices with random single precision numbers (i.e., floats). They will then output 1) the entire execution time in …

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