BL Online Training Course

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The course consists of a series of lectures on different topics in differential privacy and applications divided in two main parts. The first part of the class will focus on the basic methods to achieve differential privacy: methods based on global sensitivity, composition schemes for differential privacy, methods that use alternatives to global sensitivity, methods based on correlated noise. The second part of the class will focus on different models: differential privacy in the streaming model, multiparty models for differential privacy and some relations of differential privacy with complexity, statistics, machine learning, and adaptive data analysis. . This course is suitable for senior reasearcher/Ph.D./Matser. Online Course is 30 hours training course, wich will admit 40 excellent trainees including young researcher, Ph.D. and master students.

Syllabus

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*Introduction to Differential Privacy

*Group Privacy

*Composition

*Anonymity

*Differential Privacy Models and Algorithms

*Differential Privacy Applications

Lectures

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*Introduction to Differential Privacy

*Queries and attacks

*Randomized Response

*Composition and Histograms

*The Exponential Mechanism

*The Sparse Vector-I

*The Sparse Vector-II

*The SmallDB algorithm

*The MWEM algorithm-I

*The MWEM algorithm-II

* Gaussian Mechanism

*Differential Privacy Models and Algorithms

*Multiparty Differential Privacy

*Trainee Driector

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