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1
Intro
2
Title
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First Crypto
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Simons Institute
5
Whats Next
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Outline
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Machine Learning
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Learning or Training
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Learning Definition
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Theory of the Learner
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DNF
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Generation
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Machine Learning and Crypto
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The Problem
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The Revolutionary Impact
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Learning Parity with Noise
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Quantum Computers
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Quantum Resilience
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Theory and Practice
20
Machine Learning Practice
21
Data is the New Oil
22
Cryptography is a Field
23
Challenges
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Adversary Machine Learning
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Pig Recognizer
26
Cryptography
27
Image Classification
28
Leakage Resilient
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The Holy Grail
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Digital Privacy Laws
31
Model Tracing
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Fairness Accountability Transparency
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General Results
34
Proof of Concept
35
Pick and Choose
36
Classification
37
Computation vs Encryption
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Linear Classification
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Deep Neural Networks
40
Crypto Nets
41
Federate Learning
Description:
Explore a comprehensive IACR Distinguished Lecture by Shafi Goldwasser, presented at Crypto 2018, delving into the evolution of cryptography from concept to real-world impact. Examine the intersection of cryptography with machine learning, quantum computing, and digital privacy. Investigate key topics such as learning parity with noise, quantum resilience, adversarial machine learning, and leakage-resilient cryptography. Discover the challenges and opportunities in the field, including fairness, accountability, and transparency in AI systems. Learn about innovative concepts like crypto nets and federated learning, and understand how cryptography is adapting to address modern computational challenges and privacy concerns in the age of big data and advanced AI technologies.

From Idea to Impact, the Crypto Story - What's Next?

TheIACR
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