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Information bottlenecks in emerging distributed systems - Part 2

Plenary Talk 2022 North American School of Information Theory UCLA, Los Angeles, August 16-19, 2022.

Machines learningDistributed LearningDistributed Systems

Channel capacity (baud rate)

Quantum Information's Birth, Growth, And Significance

2021 Shannon Lecture Charles Bennett (IBM)

Shannon LecturesQuantum Information Theory

Sum Of Squares — Where Are We, And Where To Go?

�ۿ۴�ý ISIT 2020, Los Angeles (Virtual) Plenary Lecture Video image begins at 0:31

ISIT Plenary LecturePlenary LectureOptimization

Neural Augmentation In Wireless Communication

�ۿ۴�ý ISIT 2020, Los Angeles (Virtual) Plenary Lecture Video begins at 0:30

ISIT Plenary LecturePlenary LectureMachine LearningCoding Theory

Active Methods: Learning as you go and as fast as you can - Part 3

Plenary Talk 2022 North American School of Information Theory UCLA, Los Angeles, August 16-19, 2022.

Machine Learning

How internet communication works: Network Coding

Information Theory Society presents a brief history of internet communication and packet switched networks leading to the idea of network coding.…

Network Coding

Channel Coding

Winner of the ISIT 2020 Student Video Contest Students: Jeongmin Chae and Minoh Jeong

Coding TheoryChannel Coding

Coded String Reconstruction Problems

�ۿ۴�ý ISIT 2020, Los Angeles (Virtual) Plenary Lecture Video image begins at 0:30

ISIT Plenary LecturePlenary LectureInformation Theory in Biology

The Asymptotic Equipartition Property

Winner of the ISIT 2020 Student Video Contest Student: Jordi Borras and Francesc Molina

Coding Theory

The Asymptotic Equipartition Property

Winner of the ISIT 2020 Student Video Contest Students: Wael Alghamdi, Madeleine Barowsky, Boriana Gjura and Hao Wang

Coding Theory

Machine-Learning Based Approaches To Coding

�ۿ۴�ý ISIT 2020, Los Angeles (Virtual) Tutorial Lecture Video image begins at 0:35.

TutorialMachine LearningCoding Theory

The Beauty of Lempel-Ziv Compression

Information Theory Society presents how the Lempel-Ziv lossless compression algorithm works. It was published in 1978 and improved by Welch in 1984…

Source CodingCoding Theory

What is a Markov chain?

What motivated the concept of Markov chains & Markov models? Featuring Plato's theory of forms, Jacob Bernoulli's weak law of large numbers and…

Coded Computing

�ۿ۴�ý ISIT 2020, Los Angeles (Virtual) Tutorial Lecture Video image begins at 0:30

TutorialCoded Computing

Gone Fishin'

�ۿ۴�ý ISIT 2020, Los Angeles (Virtual) Plenary Lecture Video image begins at 0:15

ISIT Plenary LecturePlenary Lecture

Fundamentals Of Blockchain Systems

�ۿ۴�ý ISIT 2020, Los Angeles (Virtual) Tutorial Lecture Video image begins at 0:10

TutorialBlockchain

Morse Code

Morse Code Simulator: https://www.khanacademy.org/math/appl...

Claude Shannon: A Mathematical Theory of Communication

Claude Shannon demonstrated how to generate "english looking" text using Markov chains and how this gives a satisfactory representation of the…

What is a bit?

How can we quantify/measure an information source? We introduce the ideas of Nyquist & Hartley using a simple game involving yes/no questions. It…

Hamming and low density parity check codes

Information Theory Society presents the key concepts needed to understand low-density parity-check codes (LDPC codes). It's a blend of repetition…

LDPC CodesCoding Theory

How Recommender Systems Work

The key insights behind content and collaborative filtering (Matrix Factorization). How Amazon, Netflix, Facebook and others predict what you will…

Recommender SystemsApplications

Secret Sharing Explained Visually

The �ۿ۴�ý Information Theory Society presents an overview of Adi Shamir's 1979 paper on secret sharing. This is part of our series on the greatest…

Secrecy

How space-time codes work (MIMO)

Coding Theory

Polar Codes: Origins to 5G and Beyond - Part 1

Channel CodingCoding TheoryPolar Codes

Information Theoretic Foundations for Data Science - Part 2

Plenary Talk 2022 North American School of Information Theory UCLA, Los Angeles, August 16-19, 2022.

Machine Learning

An Information Theoretic Perspective on Database and Graph Matching - Part 1

Plenary Talk 2022 North American School of Information Theory UCLA, Los Angeles, August 16-19, 2022.

Database Graph Matching

Information bottlenecks in emerging distributed systems - Part 1

Plenary Talk 2022 North American School of Information Theory UCLA, Los Angeles, August 16-19, 2022.

Machines learningDistributed LearningDistributed Systems

Active Methods: Learning as you go and as fast as you can - Part 1

Plenary Talk 2022 North American School of Information Theory UCLA, Los Angeles, August 16-19, 2022.

Machine Learning

Polar Codes: Origins to 5G and Beyond - Part 2

Channel CodingCoding TheoryPolar Codes

An Information Theoretic Perspective on Database and Graph Matching - Part 2

Plenary Talk 2022 North American School of Information Theory UCLA, Los Angeles, August 16-19, 2022.

Database Graph Matching

Active Methods: Learning as you go and as fast as you can - Part 2

Plenary Talk 2022 North American School of Information Theory UCLA, Los Angeles, August 16-19, 2022.

Machine Learning

Community-Aware Group Testing

Plenary Talk 2022 North American School of Information Theory UCLA, Los Angeles, August 16-19, 2022.

Group Testing

Information Theoretic Foundations for Data Science - Part 1

Plenary Talk 2022 North American School of Information Theory UCLA, Los Angeles, August 16-19, 2022.

Machine Learning