COMP9417 – Machine Learning Homework 1: Regularized Regression & Statistical Estimators Introduction In this homework we will explore gradient based optimization and explain in detail how gradient descent can be implemented. Gradient based algorithms have been crucial to the development of machine learning in the last few decades. The most famous example is the backpropagation […]
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CS520 Assignment 3: Inverse Kinematics with Skinning Due Monday April 17, 2023, by 11:59pm Instructions In this assignment, you will implement skinning, forward kinematics (FK) and inverse kinematics (IK) to deform a character. The character is represented as an obj mesh. We provide ASCII files for skinning weights and skeleton data. Our starter code can
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COMP9417 – Machine Learning Homework 2: Classification models – Regularized Logistic Regression and the Perceptron Introduction In this homework we first look at a regularized version of logistic regression. You will im- plement the algorithm from scratch and compare it to the existing sklearn implementation. Special care will be taken to ensure that our implementation
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1. People with a virtual machine or laptop may be limited in their choice of optimizations (e.g. you will not be able tr deal with placement). 2. Please make appropriate assumptions: a. Define an appropriate workload (what data you will use), how you will input it etc. b. Define how you will measure the performance,
CS6601 Midterm – Spring 2020 Please read the following instructions thoroughly. Fill out this PDF form and submit it on Gradescope and then on Canvas for backup purposes. You have unlimited resubmissions until the deadline. You can: (a) type directly into the form – we highly recommend using Adobe Reader DC (or Master PDF on
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CS 6601 Artificial Intelligence Fall Semester 2022 Midterm Examination Paper Duration of Exam: 10 Oct 2022, 8:00 AM (EDT) – 17 Oct 2022, 8:00 AM (EDT) Weight: 15% No. pages: 35 No. Questions: 6 Total marks: 103 Instructions: • Before solving the exam, you should read the Ed post titled “Midterm Exam Next Week”. •
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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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CS 6601 Artificial Intelligence Spring 2023 Midterm Exam Weight: 15% of your final grade Duration of Exam: 27 Feb 2023, 8:00 AM (EDT) – 6 Mar 2022, 8:00 AM (EDT) Before solving the exam, you should read the Ed posts for any updated information or clarifications on the exam. You have an unlimited number of
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cs211 Programming assignment 2 (150 points) Programming assignment 2 (150 points) Start Assignment Due Friday by 10pm Points 150 Submitting a file upload File Types tar Available Feb 12 at 12am – Mar 3 at 11:59pm Stacks, Queues, Trees, Graph algorithms in C (150 points, approximately 12.5% of course grade) Prof. Yipeng Huang Rutgers University
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EECE5644 Introduction to Machine Learning and Pattern Recognition HW3 Question 1 (60%) In this exercise, you will train many multilayer perceptrons (MLPs) to approximate class label posteriors. The MLPs will be trained using maximum likelihood parameter estimation (or equiva- lently, minimum average cross-entropy loss). You will then use the trained models to approximate a maximum
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