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.

Local behavior of divergence

Speaker: 

Amirhossein Taghvaei

Institution: 

UC Irvine

Time: 

Tuesday, February 18, 2020 - 2:00pm to 2:50pm

Location: 

RH 510R

This week, we will discuss Section 4.2-4.3 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.

Convexity of Information Measures

Speaker: 

Amirhossein Taghvaei

Institution: 

UC Irvine

Time: 

Tuesday, February 11, 2020 - 2:00pm to 2:50pm

Location: 

RH 510R

This week, we will discuss Section 4.1 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.

Continuity of divergence

Speaker: 

Liam Hardiman

Institution: 

UC Irvine

Time: 

Tuesday, February 4, 2020 - 2:00pm to 2:50pm

Location: 

RH 510R

This week, we will discuss Section 3.5 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.

Variational characterizations of divergence: Donsker-Varadhan

Speaker: 

Kathryn Dover

Institution: 

UC Irvine

Time: 

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

Location: 

RH 510R

This week, we will discuss Section 3.3 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.

Geometric interpretation of mutual information

Speaker: 

Sonky Ung

Institution: 

UC Irvine

Time: 

Tuesday, January 21, 2020 - 2:00pm to 2:50pm

Location: 

RH 510R

This week, we will discuss Section 3.2 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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