The ACAIN-LOD 2021 Springer LNCS Volume Numbers are the following 13163 and 13164.
Author: giuseppe
ACAIN 2021 Best Paper Award
ACAIN 2021 Best Paper Award:
“Effect of Geometric Complexity on Intuitive Model Selection”
Eugenio Piasini, Vijay Balasubramanian & Joshua Gold
Computational Neuroscience Initiative, University of Pennsylvania, USA.
Zoom link sent
Dear LOD-ACAIN 2021 Lecturers, Authors and Attendees,
the past few days, we sent the Zoom link.
Please check your inbox (Spam box too).
Program:
https://lod2021.icas.cc/wp-content/uploads/sites/16/2021/09/LOD-ACAIN-2021-Program-V1.pdf
Posters:
https://lod2021.icas.cc/wp-content/uploads/sites/16/2021/09/poster-LOD-2021-1.png
See you, in 2D or 3D, on October 4 at 14:45 BST!
LOD-ACAIN 2021 Organizing Committee.
ACAIN – LOD 2021 Program
ACAIN – LOD 2021 Program: LOD-ACAIN-2021-Program-V1
ACAIN 2021: Co-located Event @ LOD 2021
On behalf of the Organizing Committee, we are proud to announce that the ACAIN 2021, will be a co-located event at LOD 2021.
The co-located event, ACAIN 2021, will be held in conjunction with LOD 2021.
So if you register for LOD 2021 you will also be able to participate in ACAIN 2021 and vice versa.
The 7th Int. Conf. on Machine Learning, Optimization & Data Science – LOD 2021, October 5-8, 2021 – Grasmere, Lake District, England – UK
An Interdisciplinary Conference: Machine Learning, Optimization, Big Data & Artificial Intelligence without Borders
ACAIN 2021: an Online & Onsite Event!
After numerous discussions, we have concluded that holding the event this year in hybrid form, both onsite and virtual as this is most beneficial for the ACAIN community rather than postponing the conference to 2022.
The organizing committee of ACAIN 2021 has decided to run the advanced course and symposium on the scheduled dates (October 4-8, 2021), and to run it as a hybrid event:
The Wordsworth Hotel & SPA in Grasmere – Lake District England (our conference venue) has enough space to obey the safety rules (put in place due to COVID-19). To accommodate a large number of participants, we are offering the option for either physical presence (onsite) or virtual participation (online). We would be delighted if all authors and participants manage to attend; however, we are aware that in the current special circumstances, it is best to hold the event in hybrid mode.
The Advanced Course and Symposium, will be held in person with virtual rooms for authors and participants using a remote connection (Zoom). The lectures (e.g., live presentations or recorded ones) will also be made available online. We will make sure that the sessions also run live, such that the presenters can show and explain their results, and the attendees can ask questions and interact with the presenters. The sessions will be held one at a time which will allow participants from overseas to attend as many sessions as possible.
The keynote lectures will be recorded such that online participants can follow them either live or at any time they like to.
If the situation does not allow the event to take place in person, the event will instead be converted to a fully online mode.
Obviously, if ACAIN 2021 will be converted into a fully online event, participants who paid the onsite registration fee will be refunded the difference, and will thus only pay the online registration fee.
Finally, it is important to note that it is possible to change the mode of participation (the Registration):
from Onsite Registration → to Online Registration and similarly
from Online Registration → to Onsite Registration
We are offering the possibility to change the mode of participation to ACAIN 2021. Those who register in one mode can easily change it by 4 September (one month before the event starts).
- It is possible to take Onsite Registration and then change it to Online Registration and get a corresponding refund, but this decision must be made by 4 September.
- Similarly, you can do Online Registration and then upgrade to Onsite Registration and pay the difference (via PayPal); this decision must also be made by 4 September.
If you have any questions please write to the organizing committee: acain@icas.cc
See you (in-person or virtually – in 3D or in 2D 🙂 ) in the Lake District – England in October!
The ACAIN 2021 Organizing Committee.
It is possible to change the mode of participation (the Registration): from Onsite → to Online and similarly from Online → to Onsite (by 4 September)
It is possible to change the mode of participation (the Registration):
from Onsite Registration → to Online Registration and similarly
from Online Registration → to Onsite Registration
We are offering the possibility to change the mode of participation to ACAIN 2021. Those who register in one mode can easily change it by 4 September (one month before the event starts).
- It is possible to take Onsite Registration and then change it to Online Registration and get a corresponding refund, but this decision must be made by 4 September.
- Similarly, you can do Online Registration and then upgrade to Onsite Registration and pay the difference (via PayPal); this decision must also be made by 4 September.
If you have any questions please write to the organising committee: acain@icas.cc
New Keynote Speaker: Jane Wang, DeepMind, UK
Jane Wang, DeepMind, UK
She is Senior Research Scientist at DeepMind. Her background is in computational and cognitive neuroscience, complex systems, and physics. She is interested in applying neuroscience principles to inspire new algorithms for artificial intelligence and machine learning.
New Keynote Speaker: Ila Fiete, MIT, USA
Ila Fiete, MIT, USA
Associate Investigator, McGovern Institute
Professor, Brain and Cognitive Sciences
Professor Ila Fiete uses theory, simulation, and analysis of neural data to uncover how dynamics and coding interact to enable computations involving memory and reasoning.
New Keynote Speaker: Timothy Lillicrap – DeepMind & UCL, UK
Timothy Lillicrap, Google DeepMind and UCL, UK
Timothy P. Lillicrap is a Canadian neuroscientist and AI researcher, adjunct professor at University College London, and staff research scientist at Google DeepMind, where he has been involved in the AlphaGo and AlphaZero projects mastering the games of Go, Chess and Shogi. His research focuses on machine learning and statistics for optimal control and decision making, as well as using these mathematical frameworks to understand how the brain learns. He has developed algorithms and approaches for exploiting deep neural networks in the context of reinforcement learning, and new recurrent memory architectures for one-shot learning.[1] His numerous contributions to the field have earned him a number of honors, including the Governor General’s Academic Medal, an NSERC Fellowship, the Centre for Neuroscience Studies Award for Excellence, and numerous European Research Council grants. He has also won a number of Social Learning tournaments.
https://en.wikipedia.org/wiki/Timothy_Lillicrap
https://scholar.google.co.uk/citations?user=htPVdRMAAAAJ&hl=en
https://contrastiveconvergence.net/~timothylillicrap/index.php