Connectionists: ACDL 2023, 6th Advanced Course on Data Science & Machine Learning - From Deep Learning to Foundation Models | June 10-14 | Riva del Sole Resort & SPA - Italy -> Early Registration: by May 23 * Hurry up! There are only few free places left! *

[ICAS Organizing Committee]

* Apologies for multiple copies. Please forward to anybody who might be
interested *

*** Hurry up! There are only few free places left! ***

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 at 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 at 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.



*6th Advanced Course on Data Science & Machine Learning - ACDL2023*
10-14 June
Riva del Sole Resort & SPA, Castiglione della Pescaia (Grosseto) – Tuscany,
Italy
An Interdisciplinary Course: Big Data, Deep Learning & AI without Borders
*Early Registration: by May 23 (AoE)*
The Course is equivalent to 8 ECTS points for the PhD Students and the
Master Students attending the Course.

*9th International Conference on machine Learning, Optimization & Data
science – LOD 2023 *September 22 – 26, 2023 – Grasmere, Lake District,
England – UK
*Paper Submission Deadline: May 10*


*ACAIN 2023, the* *3rd International Advanced Course & Symposium on
Artificial Intelligence & Neuroscience*, September 22 – 26, 2023 –
Grasmere, Lake District, England – UK
FB:
https://www.facebook.com/ACAIN-Int-Advanced-Course-Symposium-on-AI-Neuroscience-100503321621692/
The Course is equivalent to 8 ECTS points for the PhD Students and the
Master Students attending the Course.
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.srv.cs.cmu.edu/pipermail/connectionists/attachments/20230520/a01a13ed/attachment.html>