Quantum Channels

Speaker: 

Tryphon Georgiou

Institution: 

UC Irvine

Time: 

Tuesday, May 26, 2020 - 2:00pm to 2:50pm

Location: 

Zoom

This week, we will discuss Quantum Channels. 

Working Group in Information Theory is a self-educational project in the department. Techniques based on information theory have become essential in high-dimensional probability, theoretical computer science and statistical learning theory. On the other hand, information theory is not taught systematically. The goal of this group is to close this gap.

Entropy Rate Maximization on Graphs

Speaker: 

Tryphon Georgiou

Institution: 

UC Irvine

Time: 

Tuesday, May 19, 2020 - 2:00pm to 3:00pm

Location: 

Zoom

This week, we continue to discuss entropy rate maximization on graphs.

Working Group in Information Theory is a self-educational project in the department. Techniques based on information theory have become essential in high-dimensional probability, theoretical computer science and statistical learning theory. On the other hand, information theory is not taught systematically. The goal of this group is to close this gap.

Entropy Rate Maximization on Graphs

Speaker: 

Tryphon Georgiou

Institution: 

UC Irvine

Time: 

Tuesday, May 12, 2020 - 2:00pm to 2:50pm

Location: 

Zoom

This week, we continue to discuss entropy rate maximization on graphs as an extension of our discussion of Section 5.4 of the lecture notes of Wu and Polyanski: 
http://people.lids.mit.edu/yp/homepage/papers.html

Working Group in Information Theory is a self-educational project in the department. Techniques based on information theory have become essential in high-dimensional probability, theoretical computer science and statistical learning theory. On the other hand, information theory is not taught systematically. The goal of this group is to close this gap.

Entropy Rate Examples

Speaker: 

Tryphon Georgiou and Liam Hardiman

Institution: 

UC Irvine

Time: 

Tuesday, May 5, 2020 - 2:00pm to 2:50pm

Location: 

Zoom

This week, we will go over examples of entropy rate to continue our discussion of Section 5.4 of the lecture notes of Wu and Polyanski: 
http://people.lids.mit.edu/yp/homepage/papers.html

Working Group in Information Theory is a self-educational project in the department. Techniques based on information theory have become essential in high-dimensional probability, theoretical computer science and statistical learning theory. On the other hand, information theory is not taught systematically. The goal of this group is to close this gap.

Entropy Rate

Speaker: 

Liam Hardiman

Institution: 

UC Irvine

Time: 

Tuesday, April 28, 2020 - 2:00pm to 2:50pm

Location: 

Zoom

This week, we will continue to discuss Section 5.4 of the lecture notes of Wu and Polyanski: 
http://people.lids.mit.edu/yp/homepage/papers.html

Working Group in Information Theory is a self-educational project in the department. Techniques based on information theory have become essential in high-dimensional probability, theoretical computer science and statistical learning theory. On the other hand, information theory is not taught systematically. The goal of this group is to close this gap.

Extremization of mutual information for memoryless sources and channels

Speaker: 

Kat Dover

Institution: 

UC Irvine

Time: 

Tuesday, April 14, 2020 - 2:00pm to 2:50pm

Location: 

Zoom

This week, we will discuss Section 5.1 of the lecture notes of Wu and Polyanski: 
http://people.lids.mit.edu/yp/homepage/papers.html

Working Group in Information Theory is a self-educational project in the department. Techniques based on information theory have become essential in high-dimensional probability, theoretical computer science and statistical learning theory. On the other hand, information theory is not taught systematically. The goal of this group is to close this gap.

Extremization of mutual information for memoryless sources and channels

Speaker: 

Kat Dover

Institution: 

UCI

Time: 

Tuesday, April 7, 2020 - 2:00pm to 2:50pm

Location: 

Zoom

This week, we will discuss Section 5.1 of the lecture notes of Wu and Polyanski: 
http://people.lids.mit.edu/yp/homepage/papers.html

Working Group in Information Theory is a self-educational project in the department. Techniques based on information theory have become essential in high-dimensional probability, theoretical computer science and statistical learning theory. On the other hand, information theory is not taught systematically. The goal of this group is to close this gap.

Extremization of mutual information

Speaker: 

Kevin Bui

Institution: 

UC Irvine

Time: 

Tuesday, March 10, 2020 - 2:00pm to 2:50pm

Location: 

RH 510R

This week, we will finish our discussion on Section 4.4 of the lecture notes of Wu and Polyanski: 
http://people.lids.mit.edu/yp/homepage/papers.html

Working Group in Information Theory is a self-educational project in the department. Techniques based on information theory have become essential in high-dimensional probability, theoretical computer science and statistical learning theory. On the other hand, information theory is not taught systematically. The goal of this group is to close this gap.

Extremization of mutual information

Speaker: 

Kevin Bui

Institution: 

UC Irvine

Time: 

Tuesday, March 3, 2020 - 2:00pm to 2:50pm

Location: 

RH 510R

This week, we will continue to discuss Section 4.4 of the lecture notes of Wu and Polyanski: 
http://people.lids.mit.edu/yp/homepage/papers.html

Working Group in Information Theory is a self-educational project in the department. Techniques based on information theory have become essential in high-dimensional probability, theoretical computer science and statistical learning theory. On the other hand, information theory is not taught systematically. The goal of this group is to close this gap.

Extremization of mutual information

Speaker: 

Kevin Bui

Institution: 

UC Irvine

Time: 

Tuesday, February 25, 2020 - 2:00pm to 2:50pm

Location: 

RH 510R

This week, we will discuss Section 4.4 of the lecture notes of Wu and Polyanski: 
http://people.lids.mit.edu/yp/homepage/papers.html

Working Group in Information Theory is a self-educational project in the department. Techniques based on information theory have become essential in high-dimensional probability, theoretical computer science and statistical learning theory. On the other hand, information theory is not taught systematically. The goal of this group is to close this gap.

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