Outline � What is Explainable AI? � Desiderata of an Explainable AI technique � Uses of Explainable AI � Methods for Explainable AI � Activation Maximization � Shapley Values � Taylor Expansions � Layer-wise Relevance Propagation 1/24 What is Explainable AI? Standard machine learning: � The function f is typically considered to be a “black-box” […]
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lecture/12-em-annotated.pdf lecture/13-poe-annotated.pdf lecture/14-xai-annotated.pdf lecture/lecture1-annotated.pdf lecture/lecture10.pdf lecture/lecture11.pdf 1/24 Outline � Latent Variable Models � The Expectation Maximization Procedure � Gaussian Mixture Models � K-Means Clustering � Kernel K-Means 2/24 Motivation PCA of Iris dataset PCA of Boston dataset PCA of Diabetes dataset PCA of Digits dataset Complex data cannot be modeled accurately by standard probability distributions
Outline � Latent Variable Models � The Expectation Maximization Procedure � Gaussian Mixture Models � K-Means Clustering � Kernel K-Means 1/24 Motivation PCA of Iris dataset PCA of Boston dataset PCA of Diabetes dataset PCA of Digits dataset Complex data cannot be modeled accurately by standard probability distributions (e.g. Gaussian) and require a more complex
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Panel Data and Diff-in-Diff Chris Hansman Empirical Finance: Methods and Applications January 25-26, 2020 1/76 Some Details First assignment released this week Posted on January 26th Due on February 9th. 2/76 Overview Last class: an introduction to causality This class: estimating causal effects with panel data 1. An introduction to
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An Introduction to Causality Chris Hansman Empirical Finance: Methods and Applications Imperial College Business School Week Two January 18, 2021 1/95 Last Week’s Lecture: Two Parts (1) Introduction to the conditional expectation function (CEF) (2) Ordinary Least Squares and the CEF 2/95 Today’s Lecture: Four Parts (1) Analyzing an experiment in R Comparing means
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Review Chris Hansman Empirical Finance: Methods and Applications Imperial College Business School March 8-9, 2021 1/102 Topic 1: OLS and the Conditional Expectation Function Consider random variable yi and (variables) Xi Which of the following is false, (a) Xi′βOLS provides the best predictor of yi out of any function of Xi (b) Xi′βOLS
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Machine Learning for Financial Data March 2021 ETHICAL & PRIVACY CONSIDERATIONS Contents ◦ Algorithmic Fairness ◦ Source of Bias ◦ Aequitas Discrimination & Bias Audit Toolkit ◦ Bias Mitigation ◦ Ethical Machine Learning ◦ Deon Data Science Ethics Checklist Copyright (c) by Daniel K.C. Chan. All Rights Reserved. 2 Ethical & Privacy Considerations Algorithmic Fairness
Math 215.01, Spring Term 1, 2021 Writing Assignment #5 Turn your le in on Pweb in pdf format under \Writing Assign- ments”. There is no need to put your name on the document since I will grade anonymously, and Pweb will keep track of the authorship of the document. You will be graded on your
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Math 215.01, Spring Term 1, 2021 Writing Assignment #3 Turn your le in on Pweb in pdf format under \Writing Assign- ments”. There is no need to put your name on the document since I will grade anonymously, and Pweb will keep track of the authorship of the document. You will be graded on your
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