Ημερολόγιο Εκδηλώσεων

THE DEPARTMENT OF ECONOMICS OF THE ATHENS UNIVERSITY OF ECONOMICS AND BUSINESS

WITH THE FINANCIAL SUPPORT OF HELLENIC FOUNDATION FOR RESEARCH AND INNOVATION

ORGANIZES AN INTERNATIONAL CONFERENCE ON

Refined Econometrics and Endogeneity

11:30 am – 17.00 pm, April 7th, 2023, Athens, Greece

Conference Venue: Athens University of Economics & Business (Troias Str Building)

Host Institution: Athens University of Economics & Business (AUEB)

Organizing committee: Dimitris Christopoulos (AUEB (IEES), Yiannis Dendramis (AUEB (Econ)) and Elias Tzavalis (AUEB (Econ))

Financial support: Hellenic Foundation for Research and Innovation under the “First call for H.F.R.I. Research Projects to support Faculty members and Researchers and the procurement of high-cost research equipment grant” (project no: HFRI-FM17-3532). 

Conference Programme (pdf)

The Sports Analytics Group of the Department of Statistics of Athens University of Economics & Business (AUEB)

announces the short course on

FOOTBALL ANALYTICS

as a part of the

7th AUEB Sports Analytics Workshop (AUEB SAW2023)

The course will be delivered by Professor Dimitris Karlis (AUEB), Prof. Ioannis Ntzoufras (AUEB) and assistant Professor Leonardo Egidi (University of Trieste).

The course will be held virtually via TEAMS on the evenings of Tuesday 2nd and Wednesday 3rd of May 2023 (possibly on 17.00-21.00, Greek time, EEST (Eastern European Summer Time), GMT+3; time and schedule will be finalised before the event).

Course Program
DAY 1
• Current topics in Football Analytics
• Double Poisson Models, Prediction, and League re-generation
• Bayesian Models for Prediction Using the footbayes R package

DAY 2
• Bayesian Models for Prediction Using the footbayes R package (continued)
• Prediction with Advanced Models
• Introduction to in-play analytics

All participants should have R installed on their computers. Some implementations will possibly be in OpenBUGS, Jags or STAN and footbayes package in R (https://github.com/LeoEgidi/footBayes)

All course participants will receive a certificate of attendance if they attend all sessions.

Webpage of the short course on Football Analytics is available here https://aueb-analytics.wixsite.com/saw2023/short-course.

Apply now here https://aueb-analytics.wixsite.com/saw2023/registration.

Early registration will be available until Sunday 23rd of April 2023.

UNESCO Chair on Digital Methods for the Humanities and Social Sciences

Seminar Series: Digital Work

Wednesday, 15 March 2023, 4:30 p.m.
Trias Building, Room 107, Trias 2 & Spetson, Athens 11362

and online via: https://www.dept.aueb.gr/el/dmh/LiveSeminar

Speakers:
Dr. Yannis Assael, Staff Research Scientist, Google DeepMind
Dr Thea Sommerschield, Marie Skłodowska-Curie fellow, Ca' Foscari University of Venice
Dr. John Pavlopoulos, Researcher, Athens University of Economics and Business

Topic: Predicting the past: AI for Ancient Greek Epigraphy

Abstract

Ancient history relies on disciplines such as epigraphy - the study of inscribed texts known as inscriptions - for evidence of the thought, language, society and history of past civilizations. However, over the centuries, many inscriptions have been damaged to the point of illegibility, transported far from their original location and their date of writing is steeped in uncertainty. In this talk we will present Ithaca, the first deep neural network for the textual restoration, geographical attribution and chronological attribution of ancient Greek inscriptions. Ithaca is designed to assist and expand the historian’s workflow. The architecture of Ithaca focuses on collaboration, decision support and interpretability. While Ithaca alone achieves 62% accuracy when restoring damaged texts, the use of Ithaca by historians improved their accuracy from 25% to 72%, confirming the synergistic effect of this research tool. Ithaca can attribute inscriptions to their original location with an accuracy of 71% and can date them to less than 30 years of their ground-truth ranges, redating key texts of Classical Athens and contributing to topical debates in ancient history. Ithaca actively demonstrates how Artificial Intelligence can unlock the cooperative potential of the Sciences and the Humanities, for a better understanding of our nature and transformationally impacting the study of one of the most significant periods in human History.

Yannis Assael

Dr. Yannis Assael is a Staff Research Scientist at Google DeepMind working on Artificial Intelligence, and he is featured in Forbes' "30 Under 30" distinguished scientists of Europe. In 2013, he graduated from the Department of Applied Informatics, University of Macedonia, and with full scholarships, he did an MSc at the University of Oxford, finishing first in his year, and an MRes at Imperial College London. In 2016, he returned to Oxford for a DPhil degree with a Google DeepMind scholarship, and after a series of research breakthroughs and entrepreneurial activities, he started as a researcher at Google DeepMind. His contributions range from audio-visual speech recognition to multi-agent communication and AI for culture and the study of damaged ancient texts. Throughout this time, his research has attracted the media's attention several times, has been featured on the cover of the scientific journal Nature, and focuses on contributing to and expanding the greater good.

Thea Sommerschield

Thea Sommerschield is a Marie Skłodowska-Curie fellow at Ca’ Foscari University of Venice. Her research uses machine learning to study the epigraphic cultures of the ancient Mediterranean world. Since obtaining her DPhil in Ancient History at the University of Oxford in 2021, she has been the Ralegh Radford Rome Awardee at the British School at Rome, Fellow in Hellenic Studies at Harvard’s Center for Hellenic Studies and Research Innovator at Google Cloud. She co-led the Pythia (2019) and Ithaca (2022) projects, and has worked extensively on Sicilian epigraphy.

John Pavlopoulos

John Pavlopoulos is a researcher currently affiliated with the Athens University of Economics and Business (AUEB) and Stockholm University (SU). Before that, he was a visiting scholar at Ca' Foscari University of Venice (Venice Centre for Digital and Public Humanities) and a senior lecturer (fixed-term) at SU. His BSc was in Applied Mathematics and Physical Sciences at the National Technical University of Athens, his MSc was in Artificial Intelligence at the University of Edinburgh, and his Ph.D. at AUEB was focused on aspect-based sentiment analysis. His research is focused on machine learning for natural language processing and his recently published work concerns opinion polarization, toxic language detection and mitigation, diagnostic captioning, Homeric computational authorship analysis, and Ithaca.

The conference is jointly organized by the Athens University of Economics and Business, Stevens Institute of Technology and the Bodossaki Foundation. The conference sessions will take place on June 19-20. 

An academic extension of the conference is being planned for June 21-23, 2023, on the island of Syros, where participants will have the opportunity to participate in invited research workshops, attend presentations of major funded research projects, engage in networking and discussions about collaborations in funded research, and participate in a Doctoral consortium.

Learn more: https://lmde2023.org/

The 19th e-Summer School in Risk Finance and Stochastics, 28 - 30 September 2022 is organized by AUEB (Departments of Accounting & Finance, Business Administration, Statistics) in collaboration with the University of the Aegean (Departments of Statistics & Actuarial-Financial Mathematics, Financial & Management Engineering).

Due to the current situation concerning the COVID 19 pandemic, the standard operation of the Summer School would be difficult, if not impossible. However, trying to stay loyal to our usual annual meeting, we decided to transform the school into e-mode, thus enabling distant participation. Surely, we will lose the joy of meeting, interacting and exchanging views, however, we hope that next year we will be able to get back to our usual modus operandi.

As always, we will have the pleasure and honour of having with us distinguished academics in the field.

Details concerning the keynote speakers as well as the program of the school will be announced after the 15th of September.

The school is addressed to postgraduate students, PhD students, postdocs, researchers and practitioners whoa are interested to stay informed about the latest developments in the field of stochastic finance.

There is no fee for attending the school, but interested participants should send an e-mail of intention to participate to masterst@aueb.gr , stating their name, capacity, affiliation and including a short cv (no more than 10 lines), by 15 September, so that the selection procedure can proceed on time.

The maximum number of participants will be 30 and among equivalent participants priority will be given to those who applied first.

The Organizing Committee

I. Baltas (Aegean),
G. Kouretas (AUEB),
G. Papayiannis (HNA),
A. Tsekrekos (AUEB),
S. Vakeroudis (AUEB)
S. Xanthopoulos(Aegean),
A.N. Yannacopoulos (AUEB)
A. Zimbidis (AUEB)

AUEB-NKUA-Indiana Conference in Biostatistics & Health Analytics

4-6 July 2022, Aegina Island

We are pleased to announce the first AUEB-NKUA-Indiana Conference on Biostatistics & Health Analytics. 

​This is within the broader collaboration between the The Fairbanks School of Public Health, the School of Public Health in Bloomington of Indiana University and the Department of Statistics of Athens University of Economics and Business and the National and Kapodistrian University of Athens School of Medicine (NKUA). 

More info: https://aueb-analytics.wixsite.com/biostats-conf

Registration: https://aueb-analytics.wixsite.com/biostats-conf/registration

ΑΙ@AUEB talk (hybrid presentation)

Tuesday, 28 June 17.15 (Greek time)

Room: Ground floor, Troias building

and virtually via MS Teams:

https://teams.microsoft.com/l/meetup-join/19%3aOiYUJgd5vTDTv9p0FnXvTdZ9TTZxIBRHwZzEpD02P-Y1%40thread.tacv2/1653150802937?context=%7b%22Tid%22%3a%22ad5ba4a2-7857-4ea1-895e-b3d5207a174f%22%2c%22Oid%22%3a%225b49c8b5-6801-409c-a8f8-6e18215b3a08%22%7d

Speaker: Stratis Ioannidis, Northeastern University, USA

Title: Spectral Algorithms for Ranking Regression

Abstract: We consider learning from rankings, i.e., learning from a dataset containing subsets of samples ranked w.r.t. their relative order. For example, a medical expert presented with patient records can order them w.r.t. the relative severity of a disease. Rankings are often less noisy than class labels: human experts disagreeing when generating class judgments often exhibit reduced variability when asked to compare samples instead. Rankings are also more informative, as they capture both inter and intra-class relationships; the latter are not revealed via class labels alone. Nevertheless, the combinatorial nature of rankings increases the computational cost of training significantly. We propose spectral algorithms to accelerate training in this ranking regression setting; our main technical contribution is to show that the Plackett-Luce negative log-likelihood augmented with a proximal penalty has stationary points that satisfy the balance equations of a Markov Chain. This observation yields fast spectral algorithms for ranking regression for both shallow and deep neural network regression models.
Compared to state-of-the-art siamese networks, our resulting algorithms are up to 175 times faster and attain better predictions by up to 26%
Top-1 Accuracy and 6% Kendall-Tau correlation over five real-life ranking datasets.

Bio: https://ece.northeastern.edu/fac-ece/ioannidis/bio.html

We are happy to announce the next (remote) AI@AUEB talk:

Date/time: Tuesday 7 June 2022, 17:15-18:00 (Greek time)
Title: "On new variants of multiplicative weights update and mirror descent methods for zero-sum games"
Speaker: Vangelis Markakis (http://pages.cs.aueb.gr/~markakis/)

Abstract:

Our work focuses on extra gradient learning algorithms for finding Nash equilibria in bilinear zero-sum games. Such algorithms tend to exhibit a stronger performance than simple gradient methods, by having an intermediate and a final gradient step in each iteration. In this talk, we will first give an overview of recently proposed learning algorithms in this context, such as the Optimistic Multiplicative Weights Update method (by Daskalakis, Panageas, 2019) and Optimistic Mirror Descent (by Mertikopoulos et al. 2019). We will then propose a new algorithm, which can be formally considered as a variant of Optimistic Mirror Descent, using a large learning rate for the intermediate gradient step (and interpreted as computing approximate best response strategies against the profile of the previous iteration). Our main theoretical result is that the method guarantees last-iterate convergence to an equilibrium. In particular, we show that the algorithm reaches first an approximate Nash equilibrium, by decreasing the Kullback-Leibler divergence of each iterate, until the method becomes a contracting map, and converges to the exact equilibrium. Furthermore, we present experimental comparisons against the optimistic multiplicative weights update method, and show that our algorithm has significant practical potential since it offers substantial gains in terms of accelerated convergence.

Paper: https://arxiv.org/abs/2106.03579

MS Teams link:

https://teams.microsoft.com/l/meetup-join/19%3aOiYUJgd5vTDTv9p0FnXvTdZ9TTZxIBRHwZzEpD02P-Y1%40thread.tacv2/1653150802937?context=%7b%22Tid%22%3a%22ad5ba4a2-7857-4ea1-895e-b3d5207a174f%22%2c%22Oid%22%3a%225b49c8b5-6801-409c-a8f8-6e18215b3a08%22%7d

ΑΙ@AUEB Lecture Series aim is to create collaborations, both between AUEB’s Departments and with external bodies and organizations, promoting the work of AUEB members, further strengthening existing collaborations, and possibly attracting additional resources.

To subscribe to the mailing list of AI@AUEB, send a message (with any subject and body) to ai_meetings-subscribe@lists.aueb.gr. To unsubscribe, send a  message (with any subject and body) to ai_meetings-unsubscribe@lists.aueb.gr. Only the organizers of AI@AUEB can post messages to the mailing list.

If you have an AUEB account, you can also subscribe to the MS Teams team "AI@AUEB" (team code: r2dtl45). This way you will be able to see the scheduled AI@AUEB talks on your MS Teams calendar. You will also be able to send messages to the members of the team.

The Sports Analytics Group of the Department of Statistics of Athens University of Economics & Business (AUEB) announces the short course on

BASKETBALL DATA SCIENCE

as a part of the

6th AUEB Sports Analytics Workshop (AUEB SAW2022)

​The course will be delivered by Professor Paola Zuccolotto and Professor Marica Manisera from University of Brescia, authors of the best seller book with the same title.

The course will be  hosted in a hybrid form (virtual and live) at AUEB, Athens (Greece) on the evenings of Monday 23rd and Tuesday 24th of May 2022 (Day 1 ~12.00-16.00, Day 2 14.00-18.00, Greek time, EEST (Eastern European Summer Time), GMT+3).

Course Program

DAY 1

12.00-16.00 Monday 23/5/2022 (Hybrid)

•             Data science in basketball

•             Basketball data

•             Introduction to the R package BasketballAnalyzeR

•             Basic statistical analyses using BasketballAnalyzeR (1/2)

DAY 2

14.00-18.00 Tuesday 24/5/2022 (Hybrid)

•             Basic statistical analyses using BasketballAnalyzeR (2/2)

•             Discovering Patterns in data

•             Finding groups in data

Bibliography

•    Paola Zuccolotto and Marica Manisera, Basketball Data Science. With Applications in R. CRC Press, 2020.

•    Marco Sandri, Paola Zuccolotto, Marica Manisera (2020), BasketballAnalyzeR: Analysis and Visualization of Basketball Data. R package version 0.5.0. https://CRAN.R-project.org/package=BasketballAnalyzeR

•    Marco Sandri, The R package BasketballAnalyzeR, in: Zuccolotto P. and Manisera M., Basketball Data Science, 2020, Chapter 6.

•    Paola Zuccolotto, Marica Manisera, Marco Sandri (2021), Alley‐oop! Basketball analytics in R, Significance, 26-31 https://doi.org/10.1111/1740-9713.01507

All participants must bring their own laptops fully charged with R and the R package BasketballAnalyzeR already installed.

How to install it: https://bdsports.unibs.it/basketballanalyzer/

For any problem, please write to basketball.analyzer.help@gmail.com

All course participants will receive a certificate of attendance if they attend in both four-hour sessions.

Early registration will be available until Sunday 15 May 2022.

Web-page of Basketball Data Science course@SAW2022 is available here https://aueb-analytics.wixsite.com/saw2022/short-course

Apply now here https://aueb-analytics.wixsite.com/saw2022/registration

Limited positions are available for live attendance at the facilities of AUEB.  

The Sports Analytics Group of the Department of Statistics of Athens University of Economics & Business (AUEB) announces the

6th AUEB Sports Analytics Workshop (AUEB SAW2022)

​which will be  hosted in a hybrid form (virtual and live) AUEB, Athens (Greece) on the evenings of Thursday 26th and Friday 27th of May 2022 (~Day 1 ~17.00-21.30, Day 2 14.00-21.00, Greek time, EEST (Eastern European Summer Time), GMT+3).

The workshop will be also accompanied by a short course on Basketball Data Science (23-24 May 2022). The short course will be held in hybrid form with a limited number of places available at the facilities of AUEB.

The workshop is dedicated to the memory of Professor Stefane Kesenne, World class Sports Economist, Pioneer in the area, mentor and a good friend of Sports Analytics Group.

The Series of Sports Analytics Workshop was originally organized because of professor Kesenne.

Topics of the workshop include:

• Mathematical and physical models in sports
• Performance measures and models
• Optimization of sports performance
• Statistics and probability models
• Match outcome models
• Competitive strategy
• Game theoretical models
• Optimal tournament design and scheduling,
• Decision support systems
• Econometrics in sport
• Analysis of sporting technologies
• Computationally intensive methods
• Financial valuation in sport

Early registration will be available until Sunday 15 May 2022.

Webpage of SAW2022 is available here https://aueb-analytics.wixsite.com/saw2022.

Apply now here https://aueb-analytics.wixsite.com/saw2022/registration. 

Limited positions are available for live attendance at the facilities of AUEB.