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IARIA Congress 2023 The 2023 IARIA Annual Congress on Frontiers in Science, Technology, Services, and Applications November 13 – 17, 2023 – Valencia, Spain
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Invitation: Please consider to contribute to and/or forward to the appropriate groups the following opportunity to submit and publish original scientific results to: IARIA Congress 2023, The 2023 IARIA Annual Congress on Frontiers in Science, Technology, Services, and Applications IARIA Congress 2023 is scheduled to be November 13 – 17, 2023 in Valencia, Spain Submission (full paper) deadline: August 10, 2023 Authors of selected papers will be invited to submit extended article versions to one of the IARIA Journals. All events will be held in a hybrid mode: on site, prerecorded videos, voiced presentation slides, pdf slides. Contribution formats:
Extended versions of selected papers will be published in IARIA Journals. Print proceedings will be available via Curran Associates, Inc. Articles will be archived in the free access ThinkMind Digital Library. The topics suggested by the conference can be discussed in term of concepts, state of the art, research, standards, implementations, running experiments, applications, and industrial case studies. Authors are invited to submit complete unpublished papers, which are not under review in any other conference or journal in the following, but not limited to, topic areas. All tracks are open to both research and industry contributions. Before submission, please check and comply with the Editorial Rules. IARIA Congress 2023 Tracks A. Learning/Social/Health/Human-Machine/Metaverse Learning: Education, Learning, Online learning, etc. B. Data/Software/Multimedia/Visualization Data: Data Science, Big/Huge Data, Data-as-a-Service, Data Visualization, Data patterns, etc. C. Systems/Cloud/Networks/Internet/IoT/Signal Systems: Software-based Systems, Autonomous Systems, Systems of Systems, Complex systems, Embedded systems, On-chip systems, Real-time systems, Scalability, etc. D. Robotics/Intelligence/Sensing/Security/Vehicles Robotics: Industrial Robotics, Humanoids, Cognitive robotics, Evolutionary swarm robotics; Robots-humans cohabitation; Mobile assistive robots, etc. E. Cities/Energy/Mobility/Wireless Smart Cities: Smart Cities Systems, Urban Planning, Urban computing, Crowd tracking, Traffic sensing, etc. |
CfP: IARIA Congress 2023 || November 13 – 17, 2023 – Valencia, Spain
May 24th, 2023 
Daniela Lopez de Luise ACDL 2023, 6th Advanced Course on Data Science & Machine Learning – From Deep Learning to Foundation Models | June 10-14 | Riva del Sole Resort & SPA > Early Registration: by May 23 * Hurry up! There are only few free places left! *
May 24th, 2023 Daniela Lopez de Luise ACDL2023, An Interdisciplinary Course: From Deep Learning to Foundation Models
If you want to learn
Transformers,
Large language models (e.g., GPT family, BERT, Megatron-Turing NLG, …)
Vision – Large-scale vision models (e.g., MAE, SimCLR, …)
Vision and language (e.g., DALL.E, ALIGN, CLIP, …)
Beyond vision and language (e.g. video, Knowledge-Graph, structured data, multilingual, …)
and much more
then take part in ACDL 2023! 😉
Riva del Sole Resort & SPA – Tuscany, Italy, June 10-14
https://acdl2023.icas.cc acdl@icas.cc
EARLY REGISTRATION: by May 23
https://acdl2023.icas.cc/registration/
Oral Presentation Submission Deadline: by May 23 (AoE)
LECTURERS:
Each Lecturer will hold up to four lectures on one or more research topics.
https://acdl2023.icas.cc/lecturers/
Luca Beyer, Google Brain, Zürich, Switzerland
Lecture 1: “Large-Scale Pre-Training & Transfer in Computer Vision and Vision-Text Models 1/2”
Lecture 2: “Large-Scale Pre-Training & Transfer in Computer Vision and Vision-Text Models 2/2”
Lecture 3: “Transformers 1/2”
Lecture 4: “Transformers 2/2”
Aakanksha Chowdhery, Google Brain, USA
Lecture 1: “PaLM-E: An Embodied Language Model”
Lecture 2: “Efficiently Scaling Large Model Inference”
Thomas Kipf, Google Brain, USA
Lecture 1: “Graph Neural Networks 1/2”
Lecture 2: “Graph Neural Networks 2/2”
Lecture 3: “Structured Representation Learning for Perception 1/2”
Lecture 4: “Structured Representation Learning for Perception 2/2”
Pushmeet Kohli, DeepMind, London, UK
Lectures: TBA
Yi Ma, University of California, Berkeley, USA
Lecture 1: “An Overview of the Principles of Parsimony and Self-Consistency: The Past, Present, and Future of Intelligence”
Lecture 2: “An Introduction to Low-Dimensional Models and Deep Networks”
Lecture 3: “Parsimony: White-box Deep Networks from Optimizing Rate Reduction”
Lecture 4: “Self-Consistency: Closed-Loop Transcription of Low-Dimensional Structures via Maximin Rate Reduction”
Gerhard Paass, Fraunhofer Institute – IAIS, Germany
Lecture 1: “Introduction to Foundation Models”
Lecture 2: “Foundation Models for Retrieval Applications”
Lecture 3: “Combining Foundation Models with External Text Resources”
Lecture 4: “Approaches to Increase Trustworthiness of Foundation Models2
Panos Pardalos, University of Florida, USA
Lecture : “Diffusion capacity of single and interconnected networks”
Qing Qu, University of Michigan, USA
Lecture 1: “Low-Dimensional and Nonconvex Models for Shallow Representation Learning”
Lecture 2: “Low-Dimensional Structures in Deep Representation Learning I”
Lecture 3: “Low-Dimensional Structures in Deep Representation Learning II”
Lecture 4: “Robust Learning of Overparameterized Networks via Low-Dimensional Models”
Zoltan Szabo, LSE, London, UK
Lecture 1: “Shape-Constrained Kernel Machines and Their Applications”
Lecture 2: “Beyond Mean Embedding: The Power of Cumulants in RKHSs”
Michal Valko, DeepMind Paris & Inria France & ENS MVA
Lecture 1: “Reinforcement learning”
Lecture 2: “Deep Reinforcement Learning”
Lecture 3: “Learning by Bootstrapping: Representation Learning”
Lecture 4: “Learning by Bootstrapping: World Models”
TUTORIAL SPEAKERS:
Each Tutorial Speaker will hold more than four lessons on one or more research topics.
Bruno Loureiro, École Normale Supérieure, France
Lectures 1-10: “Wonders of high-dimensions: the maths and physics of Machine Learning”
Varun Ojha, Newcastle University, UK
Lecture 1: “Characterization of Deep Neural Networks”
Lecture 2: “Backpropagation Neural Tree”
Lecture 3: “Sensitivity Analysis of Deep Learning and Optimization Algorithms”
https://acdl2023.icas.cc/lecturers/
PAST LECTURERS: https://acdl2023.icas.cc/past-lecturers/
ACDL 2023 VENUE:
Riva del Sole Resort & SPA
Località Riva del Sole – Castiglione della Pescaia (Grosseto)
CAP 58043 – Tuscany – Italy
p: +39-0564-928111
f: +39-0564-935607
e: events@rivadelsole.it
w: www.rivadelsole.it
https://acdl2023.icas.cc/venue/
PAST EDITIONS: https://acdl2023.icas.cc/past-editions/
REGISTRATION: https://acdl2023.icas.cc/registration/
CERTIFICATE & 8 ECTS:
PhD students, PostDocs, Industry Practitioners, Junior and Senior Academics, and will be typical profiles of the ACDL attendants.The Course will involve a total of 36–40 hours of lectures, according to the academic system the final achievement will be equivalent to 8 ECTS points for the PhD Students (and some strongly motivated master student) attending the Course.
At the end of the course, a formal certificate will be delivered indicating the 8 ECTS points.
Anyone interested in participating in ACDL 2023 should register as soon as possible.
See you in Riva del Sole in June!
Giuseppe Nicosia & Panos Pardalos – ACDL 2023 Directors.
LOD 2023 1st CfP: The 9th Int. Conf. on Machine Learning, Optimization & Data Science, September 22-26, Lake District England – Paper Submission Deadline: June 10
May 24th, 2023 Daniela Lopez de Luise LOD 2023, An Interdisciplinary Conference: Deep Learning, Foundation Models & Artificial Intelligence without Borders
Satellite Events:
International Meeting on Foundation Models
Workshop AI for Medicine
25 Tracks
PAPERS SUBMISSION:
All papers must be submitted using EasyChair:
https://easychair.org/conferences/?conf=lod2023
Paper Submission deadline: June 10 (Anywhere on Earth)
CALL FOR PAPERS: https://lod2023.icas.cc/call-for-papers/
Please prepare your paper using the Springer Nature – Lecture Notes in Computer Science (LNCS) template. Papers must be submitted in PDF.
TYPES OF SUBMISSIONS:
When submitting a paper to LOD 2023, authors are required to select one of the following three types of papers:
* long paper / Late breaking paper: original novel and unpublished work (min. 12 pages, max. 15 pages in Springer LNCS format);
* short paper: an extended abstract of novel work (min. 6 pages, max. 11 pages in Springer LNCS format);
* work for oral presentation only (no page restriction; any format). For example, work already published elsewhere, which is relevant and which may solicit fruitful discussion at the conference;
LOD 2023 KEYNOTE SPEAKERS:
Gabriel Barth-Maron, DeepMind, London, UK
Talk(s): TBA
Anthony G. Cohn, University of Leeds, UK & The Alan Turing Institute, UK
“Evaluating the Commonsense Reasoning abilities of Foundation Models”
Sven Giesselbach, Fraunhofer Institute – IAIS, Germany
“Foundation Models”
“GPT”
“OpenGPT-X and Application and Practical Training of Large Scale Language Models”
LOD / ACAIN 2023 KEYNOTE SPEAKERS:
https://acain2023.icas.cc/course-lecturers/
Aldo Faisal, Imperial College London
Karl Friston, University College London
Kenneth Harris, University College London
Rosalyn Moran, King's College London
Edmund Rolls, University of Oxford
Michael Wooldridge, University of Oxford
More Keynote Speakers TBA
PAST LOD & ACAIN KEYNOTE SPEAKERS:
https://lod2023.icas.cc/past-keynote-speakers/
https://acain2023.icas.cc/past-lecturers/
25 TRACKS: https://lod2023.icas.cc/tracks/
BEST PAPER AWARD:
Springer sponsors the LOD 2023 Best Paper Award with a cash prize of 1,000 Euro.
https://lod2023.icas.cc/best-paper-award/
PROGRAM COMMITTEE:
150+ confirmed PC members!
https://lod2023.icas.cc/program-committee/
VENUE:
https://lod2023.icas.cc/venue/
“ESCAPE THE HURRYING WORLD – The loveliest spot that man hath ever found…”
Escape to the Lake District, England – a UNESCO World Heritage site – and you’ll find it’s easy to share William Wordsworth’s delight in the area.
The Wordsworth Hotel & Spa (****)
Address: Grasmere, Ambleside, Lake District, Cumbria, LA22 9SW, England, UK
Phone: +44-1539-435592
Email: enquiry@thewordsworthhotel.co.uk
Web: www.thewordsworthhotel.co.uk
ACCOMMODATION: https://lod2023.icas.cc/accommodation/
ACTIVITIES: https://lod2023.icas.cc/activities/
WALKS in the Lake District National Park: https://lod2023.icas.cc/walks/
Submit your research work today!
https://easychair.org/conferences/?conf=lod2023
See you in the beautiful Lake District – England in September!
Best regards,
LOD 2023 Organizing Committee.
Past Editions
https://lod2023.icas.cc/past-editions/
https://www.facebook.com/groups/2236577489686309/
https://twitter.com/TaoSciences
https://www.linkedin.com/groups/12092025/
* Apologies for multiple copies. Please forward to anybody who might be interested *
lod@icas.cc
https://lod2023.icas.cc
LOD2023 Poster:
https://lod2023.icas.cc/wp-content/uploads/sites/23/2023/01/LOD-2023-poster.png
CFP: Managing Complex Computational Challenges
May 24th, 2023 Daniela Lopez de Luise Journal of Computational Methods in Sciences and Engineering
CALL FOR PAPERS
Managing Complex Computational Challenges
A huge body of methods for making large-scale simulations and analyses are produced, which are more computationally efficient, enabling a wide range of research to be less time- and memory-intensive. The proposed methods and systems can synthesize domains that integrate many concepts from deep learning, machine learning, AI and other computational techniques. Keeping the scientific value while designing computational approaches that leverage increased computational power is essential. Developing one system identifies a few significant features or facets. However, generating a large model uses innumerable parameters and infinite indicators to bring broad models that analyse multidimensional patterns and function as generic with permissible customisation. The future computational system can build newer interfaces with computers on one side, people, technologies, and domains on the other, and produce modalities. Robust techniques with insights create solution spaces with fewer computational complexities.
Advanced big data analytics offer solutions to research questions in many different disciplines. Computational techniques coupled with intelligence are more successful for complex processes in many domains, and the refining activities lead to domain precision. In recent years efficient machine learning models have been recorded that solve many complex issues in other fields.
Many approaches in research currently warrant intensive computational methods and have become more inevitable to solve research questions. Research can generate unique and highly objective scalable solutions to the complexity and understanding of how the different propositions can help product possible systems to solve the tasks with domain knowledge.
Complexity reduction leads to robustness, structured results, higher accuracy, and resolved issues and is mainly achieved by applying computational methods. The proposed special issue will address many agendas codified in the above description and, more specifically, but not limited to the below themes.
Neural models
Spatio-temporal data modelling
DL approaches to analyse patterns
Convolutional Long Short-Term Memory network
Data Transfer Framework
Data security
Data correlational dependencies
Knowledge-driven machine learning
Information and Systems Intelligence
Computational Modelling
Intelligent agent-supported processing
Intelligent control systems
Domain-specific smart models and architectures
Complex data and sparse modelling
Semantics-induced segmentation and clustering
Edge Intelligence
The important dates
Submission of Papers: May 31, 2023
Acceptance/Rejection Notification: June 30, 2023
Revised version: August 15, 2023
Issue Publication: (will be notified later)
Special Issue Editors
Pit Pichappan, PhD,
Senior Scientist
Digital Information Research Labs
Chennai. India
Ezendu Ariwa, PhD,
Professor
Warwick University
UK
Fouzi Harrag, PhD
Associate Professor
Computer Science
Ferhat Abbas University
Setif, Algeria
For further queries, please contact- pichappan@dirf.org
For Author guidelines, please visit before submission- https://www.iospress.com/catalog/journals/journal-of-computational-methods-in-sciences-and-engineering
Submission of papers https://www.socio.org.uk/SIMCCC/openconf/openconf.php
The Conference on Parsimony and Learning (CPAL 2024): Call for Papers & Participation
May 24th, 2023 Daniela Lopez de Luise
Overview
The Conference on Parsimony and Learning (CPAL) is an annual research conference focused on addressing the parsimonious, low dimensional structures that prevail in machine learning, signal processing, optimization, and beyond. We are interested in theories, algorithms, applications, hardware and systems, as well as scientific foundations for learning with parsimony. We envision the conference as a general scientific forum where researchers in machine learning, applied mathematics, signal processing, optimization, intelligent systems, and all associated science and engineering fields can gather, share insights, and ultimately work towards a common modern theoretical and computational framework for understanding intelligence and science from the perspective of parsimonious learning.
See more about the new conference’s vision: https://cpal.cc/vision/
Topics of Interest
Topics of interest include—but are not limited to—the following subject areas (Detailed: https://cpal.cc/subject_areas/):
- Models and Algorithms: parsimonious training and inference algorithms for deep networks (e.g. based on sparsity, low-rank or so); compact and efficient neural network architecture design; structured model-based deep learning; robustness/interpretability guided by parsimony principles; generative models; distributed and federated learning; efficient neural scaling; other nonlinear dimension reduction methods, etc.
- Data: modern signal models; dataset parsimony and sparse data formats; representation learning with structured data; etc.
- Theory: generalization, optimization, robustness, and approximation in deep learning rigorously relating to its implicit parsimony; theories for classical sparse coding and their connections to neural network sparsity; forgetting owing to sparsity; etc.
- Hardware and Systems: Libraries, kernels, compilers, or customized hardware accelerating sparse computation; resource-efficient learning with co-design; etc.
- Applications and Science: parsimonious AI for science and engineering; theoretical neuroscience and cognitive science foundations for parsimony; other cross-disciplinary applications; etc.
The above is a high-level overview of CPAL's focus and is not intended to be exhaustive. If you are unsure whether your paper is a good fit for the conference, feel free to contact the program chairs via email (pcs@cpal.cc).
Submission Tracks
We will have a main proceeding track (archival), and a “recent spotlight” track (non-archival). The OpenReview submission site can be found here: OpenReview-CPAL 2024. Submissions to both tracks are to be prepared using the CPAL LaTeX style files.
Proceeding track (archival): The submission and review stage is double-blind. We use OpenReview to host papers and allow for public discussions. Full proceedings papers can have up to nine pages with unlimited pages for references and appendix.
“Recent Spotlight” Track (non-archival): Submit a conference-style paper (at most nine pages, with extra pages for references) describing the work. Please also upload a short (250 word) abstract to OpenReview. OpenReview submissions may also include any of the following supplemental materials that describe the work in further detail.
- A poster (in PDF form) presenting results of work-in-progress.
- A link to an arXiv preprint or a blog post (e.g., distill.pub, Medium) describing results.
- Appendices with detailed derivations and additional experiments.
This track is non-archival and has no proceedings. We permit under-review or concurrent submissions, as well as papers officially accepted by a journal or conference within 6 months of the Submission Deadline for Recent Spotlight Track (this year Oct 10, 2023). Reviewing will be performed in a single-blind fashion (authors should not anonymize their submissions).
Notable Innovations in Our Review Mechanism: An action PC will shepherd each paper. For every accepted paper, the names of its AC and action PC will be publicly released on its OpenReview page, for accountability. For every rejected paper (excluding withdrawals), only the name of its action PC will be displayed. Reviewers will be rated and dynamically selected.
Please see more details on our website.
Important Dates
All deadlines are 11:59PM UTC-12:00 (anywhere on Earth)
- August 28th, 2023: Submission Deadline for Proceeding Track
- October 10th, 2023: Submission Deadline for Recent Spotlight Track
- October 14th, 2023: 2-Week Rebuttal Stage Starts (Proceeding Track)
- October 27th, 2023: Rebuttal Stage Ends, Authors-Reviewers Discussion Stage Starts (Proceeding Track)
- November 5th, 2023: Authors-Reviewers Discussion Stage Ends (Proceeding Track)
- November 20th, 2023: Final Decisions Released (Both Tracks)
- December 5th, 2023: Camera Ready Deadline (Both Tracks)
- January 3rd – 6th, 2024: Main Conference (In-Person, HKU Main Campus)
Keynote Speakers
- Dan Alistarh, IST Austria/Neural Magic
- Tom Goldstein, University of Maryland
- Robert D. Nowak, University of Wisconsin-Madison
- Dimitris Papailiopoulos, University of Wisconsin-Madison
- Jong Chul Ye, KAIST
- Yingbin Liang, Ohio State University
- … additional speakers will be announced soon!
Organizers and Contact
For inquiries, please contact organizers: pcs@cpal.cc