The exercises School of Computing and Information Systems COMP90038 Algorithms and Complexity Tutorial Week 5 Sample Answers 23. Consider the subset-sum problem: Given a set…
Tutorial questions: reasoning with arguments 1. Below is some knowledge that an agent has about monsters, where X is a variable that can be instantiated…
F71SM STATISTICAL METHODS Tutorial on Section 3 RANDOM VARIABLES 1. A discrete random variable X has probability mass function x012 f (x) 0.25 0.5 0.25…
This Week • Physics of image formation (light, reflectance, optics) • Geometry of image formation (camera models, projective geometry) • Digital images (digitisation, representation) •…
This Week • Low-Level Vision – from a biological perspective • Biological Visual System overview • Primary visual cortex (V1) – physiology » input selectivities…
4.1 • Discrete distributions Uniform on {1, 2, . . . , k}: parameter k a positive integer; X is the outcome in the situation…
The RETE Algorithm: Motivation Uncertainty and Bayesian Methods Learning Objectives Trace origin of Bayes’ Law Compare if … then with Bayes’ Rule Compute probabilities from…
Lecture 1: Introduction Coordination 1 Motivating example: Global logistics chains In global logistics, delivery of materials is delegated to transport companies to handle each journey…
Matching: dealing with outliers Whether a correlation-based method or a feature-based method is used, search is required to find points that are most similar. These…
COMP90038 Algorithms and Complexity Lecture 11: Sorting with Divide-and-Conquer (with thanks to Harald Søndergaard) DMD 8.17 (Level 8, Doug McDonell Bldg) http://people.eng.unimelb.edu.au/tobym @tobycmurray 2 Copyright…