deep learning深度学习代写代考

Autoencoders and their Applications COMP90073 Security Analytics , CIS Semester 2, 2021 Outline • IntroductiontoNeuralNetworks • GradientDecentLearning • Autoencodersandtheirarchitectures • DenoisingAutoencoder(DAE) • VariationalAutoencoder(VAE) COMP90073 Security Analytics © University of Melbourne 2021 Artificial Neural Networks • Acollectionofsimple,trainablemathematicalunitsthatcollectivelylearn complex functions • Givensufficienttrainingdataanartificialneuralnetworkcanapproximatevery complex functions mapping raw data to output decisions COMP90073 Security Analytics © University of Melbourne

Week 10: Adversarial Machine Learning – Vulnerabilities (Part II) Explanation, Detection & Defence COMP90073 Security Analytics , CIS Semester 2, 2021 Overview • Adversarial machine learning beyond computer vision – Audio – Natural language processing (NLP) – Malware detection • Why are machine learning models vulnerable? – Insufficient training data – Unnecessary features • How

When Models Meet Data Australian National University 1 8.1 Data, Models, and Learning • A machine learning system has three major components: • Data, models, learning • A model is obtained by learning from the training data • A prediction is made by applying a learned model on test data learning (Training) Data (Task) (Test)

Linear Regression Australian National University 1 Incremental Learning Z. Li and D. Hoiem. “Learning without forgetting.” TPAMI, 2017 Problem setting: A classifier is trained on classes 1,2,3; I have new classes 4,5,6,7; I want a new classifier that can recognize 1,2,…,7; In training the new classifier, we do not have access to the old data