Webinar DISA-DSM November 10th

6 November, 2020

The DISA-DSM group welcomes you to a webinar with Yaozhong Hu   (University Alberta, Edmonton, Canada) 10 November at 13:00 Stockholm time

Title: Numerical methods for stochastic Volterra integral equations with weakly singular kernels

Abstract: In this talk, we  will introduce  stochastic Volterra integral equations with weakly singular kernels and study the existence, uniqueness and Holder continuity of the solution. Then, we propose a  theta-Euler-Maruyama  scheme  and a Milstein scheme to solve  the equations numerically  and  we obtain the strong  rates of convergence for both schemes in L^{p} norm for any p\geq 1. For the theta-Euler-Maruyama  scheme the rate is min {1-alpha, 1\2-beta} and for the Milstein scheme the rate is min{1-alpha,1-2beta} when alpha\neq \frac 12, where 0<alpha<1, 0< beta<1\2. These  results on the rates of convergence are significantly different from that of the similar schemes for the stochastic Volterra integral equations with regular  kernels. The difficulty to obtain our results is the lack of Ito formula for the equations. To get around of this difficulty we use instead the Taylor formula and then carry a sophisticated  analysis on the equation the solution satisfies.

For more information and registration contact Nacira Agram – nacira.agram@lnu.se

Upcoming seminars:

  • 17 November  at 13:00 – Paolo Di Tella (University of Technology Dresden, Germany) Title: On enlarged filtrations of point processes
  • 24 November  at 12:00 – David SISKA (University of Edinburg, UK)
  • 24 November  at 13:00 WEINAN E  (Princeton University, USA) Title: An Overview of Deep Learning Based Algorithms for high dimensional PDEs Abstract: I will give an overview of deep learning-based algorithms for PDEs. Topics to be covered includes: (1) The Deep BSDE method. (2) Applications to control theory. (3) Theoretical advances.
  • 30 November at 15:00 Jiequn Han (Princeton University, USA)
  •  8 December at 13:00 Stockholm time Mathieu Lauriere (Princeton University, USA)

Keynote: Anders Arpteg: How will the recent AI-revolution change our society?

4 November, 2020

During the Big Data Conference on December 3-4, 2020 we will have a several interesting Keynote speakers, one of them is Anders Arpteg, who is the Head of research at Peltarion

He will talk about that something extraordinary has happened within AI in recent years. Companies are starting to talk about moving into an AI-first future, but what does that mean? Not only are we seeing significant scientific advances in AI, but we are also seeing companies and politicians starting to invest heavily in AI. In order to stay one step ahead, we must be prepared for what is coming next. What has really happened in recent years, and what are the next steps and trends in machine learning? What should companies know to be prepared for the rapid development that is happening with ML and AI? This talk will give a glimpse into the future of AI, what possibilities it holds, and describe concrete real-world examples of how companies such as Spotify, Peltarion, and more are using the latest AI techniques.

Don’t miss out on the opportunity to listen to him and take part of the conference by signing up here by November 25th.

Anders Arpteg

More information about Anders Arpteg
Anders Arpteg (Ph.D., Head of Research at Peltarion) has been working with AI for 20 years in both academia and industry, with a Ph.D. in AI from Linköping University. Worked at Spotify for many years making use of big data and machine learning techniques to optimize the user experience. Now heading up a research team at Peltarion, operationalizing the latest and greatest AI techniques. At Peltarion, we have the ambitious goal of making deep learning and the latest AI techniques available for all companies, not just the large technology organizations. Also a member of AI Innovation of Sweden’s steering committee, AI adviser for the Swedish government, member of the Swedish AI Agenda, member of the European AI Alliance, founder of the Machine Learning Stockholm meetup group, and member of several advisory boards.

Seminar November 3rd Solving mean-field PDE with symmetric neural networks

29 October, 2020

Welcome to the next talk related to Webinar DISA-DSM: stochastic analysis, statistics and machine learning, which is held by Huyên Pham (University Paris 7 Diderot, France)

When? 3 November at 13:00 Stockholm time.
Online via zoom: Contact Nacira Agram, nacira.agram@lnu.se, to get the link

Title: Solving mean-field PDE with symmetric neural networks
Abstract: We propose numerical methods for solving non-linear partial differential equations (PDEs) in the Wasserstein space of probability measures, which arise notably in the optimal control of McKean-Vlasov dynamics.
The method relies first on the approximation of the PDE in infinite dimension by a backward stochastic differential equation (BSDE) with a forward system of N interacting particles. We provide the rate of convergence of this finite-dimensional approximation for the solution to the PDE and its Lions-derivative. Next, by exploiting the symmetry of the particles system, we design a machine learning algorithm based on certain types of neural networks, named PointNet and DeepSet, for computing simultaneously the pair solution to the BSDE by backward induction through sequential minimization of loss functions. We illustrate the efficiency of the PointNet/DeepSet networks compared to classical feedforward ones, and provide some numerical results of our algorithm for the examples of a mean-field systemic risk and a mean-variance problem.
Based on joint work with M. Germain (LPSM, EDF) and X Warin (EDF).

We will book a room at LNU for those who wants to attend physically the seminar. Because of space restrictions due to Covid-19, please let me know if you want to do that.

A warm welcome!

Webinar DISA-DSM: stochastic analysis, statistics and machine learning

26 October, 2020

Our new DISA-group Deterministic and Stochastic Modelling (DSM) invites you to a seminar on Tuesday 27th at 13.00, this seminar is a part of a seminar series so keep an eye out for more information.

Title: Rare events simulation: least-squares Monte Carlo method vs deep learning based shooting method

Speaker: Omar Kebiri (University B-TU Cottbus-Senftenberg, Germany)

Abstract: When computing small probabilities associated with rare events by Monte Carlo it so happens that the variance of the estimator is of the same order as the quantity of interest. Importance sampling is a means to reduce the variance of the Monte Carlo estimator by sampling from an alternative probability distribution under which the rare event is no longer rare. Determine the optimal (i.e. zero variance) changes of measure leads to a stochastic optimal control problem. The control problem can be solved by a stochastic approximation algorithm, using the Feynman-Kac representation of the associated dynamic programming equations which leads to an FBSDE, and we discuss numerical aspects for high-dimensional problems along with simple toy examples using two methods: least-squares Monte Carlo method and deep learning based shooting method.
Joint work with Carsten Hartmann, Lara Neureither, and Lorenz Richter.

Practical information: We will book a room at LNU for those who wants to attend physically the seminar. Because of space restrictions due to Covid-19, please let me know if you want to do that, otherwise a link will be provided. Contact Nacira Agram – nacira.agram@lnu.se for more information.

Call for presentations, Big Data Conference 2020

23 October, 2020

A fast-forward (FF) + virtual poster (VP) sessions will be organized as part of the Big Data Conference 2020. In the FF presentations, each participant gets to show a 3-minute video to briefly summarize her/his research. Directly after the FF,  participants will be redirected to breakout rooms where it will be possible to present their VP and interact with the interested public.

The FF+VP presentations can focus on either ongoing research or new ideas:

1) Ongoing research will focus on research recently published or at an advanced stage of elaboration. The main goal here is to present research results of general interest for the public of the conference and eventually receive feedback on ongoing work.

2) New ideas will focus on future research, plans, or simply new ideas. The goal here is to share with the public their own plans, receive feedback, find partners and possibly find synergies to develop future research together.

 Submission

To submit to the FF+VP session, participants should submit a 500-word abstract briefly presenting the research by November 9th, 2020 to Diana Unander, diana.unander@lnu.se  Each participant can submit at most two abstracts.

Acceptance information will be sent out by November 13th, 2020.

If accepted, a video (in videos in 720p and mp4 format) of maximum 3 minutes should be sent by November 24th, 2020.

For more information or questions, please contact:

Are you using Twitter? Contribute to our research!

28 September, 2020

Dear Recipient,

We study the concept of similarity on Twitter and how similarity depends on the user profile, activity, and the structure of one’s social networks. This study is multidisciplinary between computer science and the humanities.

If you have a Twitter account, we kindly ask you to go to the link below and participate in this survey.

https://bit.ly/2RXhkY0

It is noteworthy that there are no correct answers in this survey, and we are only collecting data anonymously for fundamental research purposes.

Thanks in advance,

Research Team

Call for contributions: Journal of Data and Information Science

21 April, 2020

Call for contributions to a Special Issue on Open Government Data (OGD) for Data Analytics and Knowledge Discovery

We are pleased to announce the Call for Contributions to a Special Issue of Journal of Data and Information Science (JDIS) on Open Government Data (OGD) for Data Analytics and Knowledge Discovery. JDIS, a quarterly English language research journal, aims to publish basic and applied research on data-driven analytics for knowledge discovery, is edited by an international team of experts in the fields, and is indexed by ESCI and Scopus. The special issue intends to publish as the 4th issue of 2020.

Co-Guest-Editors-in-Chief for the special issue: Koraljka Golub, Fredrik Hanell, Guangjian Li, Arwid Lund. Read the rest of this entry »

Programming languages for data-Intensive HPC applications: A systematic mapping study

18 March, 2020

Don’t miss out on this publication by Sabri Pllana and other researchers.

A major challenge in modelling and simulation is the need to combine expertise in both software technologies and a given scientific domain. When High-Performance Computing (HPC) is required to solve a scientific problem, software development becomes a problematic issue. Considering the complexity of the software for HPC, it is useful to identify programming languages that can be used to alleviate this issue.

Because the existing literature on the topic of HPC is very dispersed, we performed a Systematic Mapping Study (SMS) in the context of the European COST Action cHiPSet. This literature study maps characteristics of various programming languages for data-intensive HPC applications, including category, typical user profiles, effectiveness, and type of articles.

For more information about the publication see: https://www.sciencedirect.com/science/article/pii/S0167819119301759?via%3Dihub

Workshop on Knowledge Organization for Digital Humanities, March 27th

11 March, 2020

As a satellite event to the world’s annual iConference taking place in Sweden this year, on 27 March LNU’s iInstitute will host a workshop on knowledge organization for digital humanities.

Place: K2054V
Time: 27 March, 9-13

Programme:
9.00 – 9.15 Coffee available
9.15 – 09.30 Introduction to the workshop and participants
09.30 – 10.15 Shigeo Sugimoto: Metadata for Digital Humanities – An Overview
10.15 – 11.00 Atsuyuki Morishima: Combining the Power of the Crowd and AI
11.00 – 11.15 Coffee break
11.00 – 11.45 Shigeo Sugimoto: Long-term Use of Humanities Data Resources
11.45 – 12.30 Heather Moulaison-Sandy: Research Data Management in the Humanities

Please email koraljka.golub@lnu.se if you plan to attend, by Monday 23 March. Thank you!

Welcome!

For more information contact:
Koraljka Golub
Professor
Head of the iInstitute
Digital Humanities Initiative Co-Leader
Linnaeus University
http://lnu.se/personal/koraljka.golub

PhD course INNOVATIVE APPLICATIONS OF RESEARCH AND SCIENCE (4.5 credits)

6 March, 2020

The findings, experiences, and ideas that emerge from research have traditionally been utilized through academic publication and teaching programmes. However, academic impact alone is no longer enough for a successful research career. With the growing emphasis in the research funding landscape on maximizing impact beyond academia, it is increasingly important that researchers reach wider society by embedding non-academic impact strategies in their projects, by working with a range of non-academic partners, and by using ever more innovative methods of dissemination and utilization. This course showcases a range of approaches researchers can employ to ensure that their research has impact and relevance beyond universities. It will also provide students with tools that will help them best communicate the value of their work to research funders and potential investors.

How to Apply?
Opens 2nd March at 9:00 AM. Please send your application to fyrklovern.doktorand@kau.se by 11th May. You should provide your name, department, contact details, and a short description (max. 100 words) of your research project. Please ensure that you obtain your supervisor’s approval for attending the course, and also state their name in your application email.

Eligibility and further details
The course is offered to PhD students in all disciplines from Karlstad University, Linnaeus University, Mid Sweden University and Örebro University. The course consists of three mandatory sessions in the autumnof 2020 (at Karlstad, Sundsvall, and Stockholm). The course syllabus has been evaluated and approved by the Research Education Committee at Karlstad University’s Faculty of Humanities and Social Sciences. The innovation office Fyrklövern covers the cost of your course travel and accommodation. The course is taught in English.

The syllabus at https://libra.sae.kau.se/course/att-nyttiggora-forskningoch-vetenskapinnovative-applications-research-andscience

For more information contact: Martina Lago, Innovation Advisor, martina.lago@lnu.se or 0480-446062
PhD-course 2020