[DP#2] Database anonymization – differential privacy
I explain the mathematical foundations and Laplacian noise of differential privacy.
GT & DP
[DP#1] Database anonymization – k-anonymity, l-diversity, t-closeness
I expand on the concept of k-anonymity and l-diversity with a further improvement called t-closeness.
Protected: Differential Privacy
There is no excerpt because this is a protected post.
Hidden Markov Models & three key Problems and Algorithms
This is a compilation of a series of videos in which Prof. Patterson describes the Hidden Markov Model, starting with the Markov Model and proceeding to the three key questions for HMMs. A Hidden Markov Model is a machine learning model for predicting sequences of states from indirect observations.
Game Theory 11 – chap22. Job-market signaling
Learn about the first application of signaling, job-market signaling by Michael Spence.
Game Theory 11 – chap21. Forward induction and Cho-Kreps’ intuitive criterion
Learn how to refine the various PBEs in a signaling game using forward induction.
Game Theory 10 – chap20. Computing PBE in signaling games
Describe how to find a PBE in a signaling game.
Game Theory 10 – chap19. Signaling games intro
Introduce signaling games and explain how PBEs are defined in these games.
Game Theory 10 – chap18. Perfect Bayesian Equilibrium
Define a perfect Bayesian equilibrium (PBE), explain its existence, how it relates to existing equilibria (NE/SPE), and finally how this relationship can be used to find a PBE.
Game Theory 10 – chap17. Sequential rationality in games of imperfect information
We explain how to define sequential rationality in dynamic Bayesian games and why traditional equilibria (SPE or NE) do not satisfy sequential rationality.