CSoI-UJ 2023 Seminar Series: Dynamic Networks, Machine Learning, AI for Classical and Quantum Data
When: November 6 till November 24 every day at 17:00 EU time and 11am EST USA time.
All lectures are recoreder and can be viewed on CSoI YouTube playlist containing all videos of this seminar series.
For personal discussion at the beginning and the end of the seminar, we shall use the following zoom: https://purdue-edu.zoom.us/j/548154976
A three week seminar series by CSoI together with faculty and students at Jagiellonian University, Poland .
The following unpublished yet book will be used and students are encouraged to brose through it:
"Analytic Information Theory: From Compression to Learning" by M. Drmota and W. Szpankowski
(see https://www.cs.purdue.edu/homes/spa/temp/ait22.pdf )
The following two books will be useful:
1 "Analysis of Algorithms on Sequences" by W. Szpankowski, Willey 2001
(see https://www.cs.purdue.edu/homes/spa/mybook.pdf).
2 "Analytic Pattern Matching: From DNA to Twitter", by P. Jacquet and W. Szpankowski
(see https://www.cs.purdue.edu/homes/spa/temp/words15.pdf)
Nov 6 , at 11:00/17:00
W. Szpankowski (Purdue) and K. Turowski (UJ)
Organizational Meeting, pls use this zoom: : https://purdue-edu.zoom.us/j/548154976
Nov 7 at 11:00/17:00
W. Szpankowski (Purdue)
"Structural and Temporal Information"
View Video of the Seminar
Nov 8, at 11:00/17:00
A. Magner (U. Albany, NY)
"Fundamental Limits of Deep Graph Convolutional Networks for Graph
Classification"
View Video of the Seminar
Nov 9 at 11:00/17:00. At 11am please use zoom : https://purdue-edu.zoom.us/j/548154976
W. Szpankowski (Purdue)
Online & Supervised Learning: Analysis and Algorithms
View Video of the Seminar
Nov 10 at 11:00/17:00
K. Turowski (UJ)
Dynamic Networks: Duplication Divergence Model - Part I
View Video of this seminar
Nov 13 , at 11:00/17:00
K. Turowski (UJ)
Dynamic Networks: Duplication Divergence Model - Part II
View Video of this seminar
Nov 14 at 11:00/17:00
A. Padakandla (U. Tennessee, Knoxville)
Introduction to Quantum Information and Computation
View Video of this seminar
View also the Quantum Computing Workshop
Nov 15 at 11:00/17:00
A. Padakandla (U. Tennessee, Knoxville)
Learning of Quantum Measurement Classes
View Video of this seminar
Nov 16 at 11:00/17:00
M. Heidari (Purdue)
Feature Selection With Discrete Fourier Expansion
View Video of this Seminar
Nov 17 at 11:00/17:00. At 11am pls use zoom: : https://purdue-edu.zoom.us/j/548154976
M. Heidari (Purdue)
Physically Realizable Quantum Algorithms
View Video of this Seminar
Nov 17 at 11:00/17:00
M. Heidari (Purdue)
“Toward Physically Realizable Quantum Algorithms”
View Video of this Seminar
Nov 20-23 at 11:00/17:00
Students' zoom seminar, use https://purdue-edu.zoom.us/j/548154976
Potential topics are listed below. Please discuss before with prof. K. Turowski if you are interested in any of below topic:
1. The degree distribution and diameter for the preferential attachment model:
a. compare methods in Bollobas, Riordan - Mathematical results on
scale-free random graphs and Bollobas et al. - The Degree Sequence of
a Scale-Free Random Graph Process
Bonus: apply differential equation method from Bennett, Dudek - A
gentle introduction to the differential equation method and dynamic
concentration to the master equation (17.1) for PA model from Frieze,
Karonski - Introduction to Random Graphs
2. Counting chordal and split graphs
a. compare Bender, Richmond, Wormald - Almost all chordal graphs
split and Troyka - Split graphs: combinatorial species and asymptotics
Bonus: apply binomial sums method from Szpanowski, Weinberger -
Minimax Pointwise Redundancy for Memoryless Models Over Large
Alphabets to obtain precise asymptotics on the number of chordal and split graphs
3. The power law in partial duplication model
a. explain derivations from Jacquet et al. - Power-law degree
distribution in the connected component of a duplication graph
Bonus: check power law hypothesis for the duplication model from
Chung, Lu - Complex Graphs and Networks, section 4.5 + use Mellin
transform to the equation (4.5)
4. Discuss parameter estimation in duplication models
a. refer the results from Sreedharan et al. - Revisiting parameter
estimation in biological networks: Influence of symmetries
Bonus: compute exact asymptotics of clustering coefficient (local and
global) for Pastor-Satorras model e.g. using differential equation
method from Bennett, Dudek - A gentle introduction to the differential
equation method and dynamic concentration
5. The degree distribution, power law, and concentration for the linear copying model
a. see Kumar et al. - Stochastic models for the web graph + provide
proofs for general d
Bonus: extend the analysis to the case, when we do not distinguish
between in- and out-degrees during copying
6. Number of isolated vertices, cherries, twins, and the asymmetry and entropy for Erdos-Renyi graphs
a. for the latter refer to Choi, Szpankowski - Compression of
graphical structures: Fundamental limits, algorithms, and experiments
Bonus: provide a similar analysis for the special case of
Pastor-Satorras model with p = 0