Corpus on Robust PCA via Low-rank and Sparse Decomposition

June 24th, 2025 Daniela Lopez de Luise
This email is to inform you about the corpus that I have created on  Robust PCA via Low-rank and Sparse Decomposition containing more than 1100 references.

The link to these corpus are DLAM Website and DLAT Website.

Thierry BOUWMANS
Ass. Pr. (HDR) – ACM Member, IEEE Senior Member

Laboratoire MIA

La Rochelle Université

France 

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Digital Data Processing 2025-IEEE

June 24th, 2025 Daniela Lopez de Luise
Fifth International Conference on Digital Data Processing (DDP 2025)
University of Bedfordshire. Luton. (Near London) UK.
August 18-20, 2025
(www.socio.org.uk/ddp)
(IEEE Publication)
(Virtual Presentation/Physical)

As technology advances in different sub-domains of computing,
data-driven models are becoming increasingly important. The
data-dependent world now faces many challenges in terms of data accuracy
and data privacy. High-impact advancements include machine learning,
artificial intelligence, deep learning and many more. Data is growing
exponentially in terms of diversity and complexity. One organization or
industry processes over a few million transactions per hour and stores
hundreds of billions of data. We live in a world with a great need for
more efficient data analysis and processing. Data analytics can reveal
hidden patterns, complex relationships, internal information relations,
and even segmentation. Data applications have opened up new
possibilities in every aspect of our lives. Studying data and its
structure, dynamics, and modern data technologies is an ongoing process.
There is a great deal of literature and research on data management, but
it does not address the data processing needs. Many studies focus on
developing models and systems for analysing large datasets.

Data analysis leads to application domains that have a systematic impact
on decisions. The knowledge gained from the data analysis enables the
generation of critical information for multiple domains. In this
conference, we review and discuss the latest trends in data management,
the opportunities and challenges, and how they have affected
organizations' ability to develop effective business and technology
strategies and stay up-to-date in data technology. We also highlight
current open research directions in data analytics that need further
attention.

The proposed conference will discuss topics not limited to

Data applications in various domains and activities
Data in cloud
Real-world data processing
Data inaccuracy and reliability issues
Data Ecosystem
Business Analytics
New data analytics techniques
Physical and management challenges
Synthetic data
Data synthesis
Crowdsourcing and Sensing
Data modelling
Deep learning techniques
Data fusion
Descriptive analytics, Diagnostic analytics, Predictive Analytics, and
Prescriptive analytics
Machine learning impact on data processing
Network optimization
Data in Biomedical Engineering
Data in Materials science and mechanics
Data handling and applications in domains
Wireless Networking Data Management
Data of Electronic & Embedded Systems
Multi-media Systems Data
Artificial Intelligence Models and Systems Data
E-Computing Data
Renewable Energies Data

General Chair

General Chair
Ezendu Ariwa
Warwick University, UK

Program Chairs
Youshan Zhang, Yeshiva University, USA
Simon Fong, University of Macau, Macau
Duong Van Hieu, Tien Giang University, Vietnam

Program Co-chairs
Martin Lopez Nores, University of Vigo, Spain
Frankie Wilson, University of Oxford. UK

Publicity Chair
Mohsin Beniysa, Abdelmalek Essaâdi University, Morocco

Publications

All accepted and presented papers will be submitted to IEEE Xplore for
publication and indexing.

The DDP 2025 has co-located workshops.

Modified versions of the papers will appear in the following journals.

Journal of Digital Information Management
International Journal of Computational Linguistics
Performance Measurements and Metrics

Important Dates

Submission of Papers:   July 216, 2025
Notification of Acceptance/Rejection:   August 10, 2025
Camera-ready:   August 31, 2025
Registration:   August 15, 2025
Conference Dates:   August 18-20, 2025
Post-Conference Proceedings Release:   November 30, 2025

Paper submission

Papers should follow the IEEE template. Submissions at
http://socio.org.uk/ddp/paper-submission/

Contact: ddp@socio.org.uk

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ICIAP 2025 Early Registration Deadline is June 30 – Register and Book Your Accommodation

June 24th, 2025 Daniela Lopez de Luise
;word-spacing:0px”> Early Registration

By registering before this date, you can take advantage of significantly reduced fees. Your registration provides full access to an exciting program, including world-class keynote speakers, technical sessions, workshops, and our social events, offering invaluable networking opportunities with peers in the beautiful city of Rome.

Register here to secure your early rate: https://www.iciap.org/registration

Plan Your Stay in Rome

As you arrange your travel, we encourage you to book your accommodation soon. We have secured special rates with a selection of nearby hotels to ensure your stay is both comfortable and convenient. Given that Rome is a top travel destination, we recommend booking your room as early as possible to guarantee availability and benefit from the conference discounts.

For a list of partner hotels and instructions on how to book with the special ICIAP 2025 rate, please visit our accommodation page: https://www.iciap.org/attending/accomodation

We are incredibly excited about the program we have put together and look forward to welcoming you to a vibrant and inspiring conference in Rome.

Best regards,

The ICIAP 2025 Organizing Committee

 

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DeepLearn 2025: regular registration July 18

June 24th, 2025 Daniela Lopez de Luise
******************************************************

12th INTERNATIONAL SCHOOL ON DEEP LEARNING
(with a special focus on Large Language Models, Foundation Models and Generative AI)

DeepLearn 2025

Porto – Maia, Portugal

July 21-25, 2025

******************************************************

Co-organized by:

University of Maia

Institute for Research Development, Training and Advice – IRDTA
Luxembourg/London

******************************************************

Regular registration: July 18, 2025

******************************************************

SCOPE:

DeepLearn 2025 will be a research training event with a global scope aiming at updating participants on the most recent advances in the critical and fast developing area of deep learning. Previous events were held in Bilbao, Genova, Warsaw, Las Palmas de Gran Canaria, Guimarães, Las Palmas de Gran Canaria, Luleå, Bournemouth, Bari, Las Palmas de Gran Canaria and Porto.

Deep learning is a branch of artificial intelligence covering a spectrum of current frontier research and industrial innovation that provides more efficient algorithms to deal with large-scale data in a huge variety of environments: computer vision, neurosciences, speech recognition, language processing, human-computer interaction, drug discovery, biomedicine and health informatics, medical image analysis, recommender systems, advertising, fraud detection, robotics, games, business and finance, biotechnology, physics experiments, biometrics, communications, climate sciences, geographic information systems, signal processing, genomics, materials design, video technology, social systems, earth and sustainability, etc. etc.

The field is also raising a number of relevant questions about robustness of the algorithms, explainability, transparency, interpretability, as well as important ethical concerns at the frontier of current knowledge that deserve careful multidisciplinary discussion.

Most deep learning subareas will be displayed, and main challenges identified through 18 four-hour and a half courses, 2 keynote lectures, 1 round table and a hackathon competition among participants. Renowned academics and industry pioneers will lecture and share their views with the audience. The organizers are convinced that outstanding speakers will attract the brightest and most motivated students. Face to face interaction and networking will be main ingredients of the event. It will be also possible to fully participate in vivo remotely.

DeepLearn 2025 will place special emphasis on large language models, foundation models and generative artificial intelligence.

ADDRESSED TO:

Graduate students, postgraduate students and industry practitioners will be typical profiles of participants. However, there are no formal pre-requisites for attendance in terms of academic degrees, so people less or more advanced in their career will be welcome as well.

Since there will be a variety of levels, specific knowledge background may be assumed for some of the courses.

Overall, DeepLearn 2025 is addressed to students, researchers and practitioners who want to keep themselves updated about recent developments and future trends. All will surely find it fruitful to listen to and discuss with major researchers, industry leaders and innovators.

VENUE:

DeepLearn 2025 will take place in Porto, the second largest city in Portugal, recognized by UNESCO in 1996 as a World Heritage Site. The venue will be:

University of Maia
Avenida Carlos de Oliveira Campos – Castêlo da Maia
4475-690 Maia
Porto, Portugal

STRUCTURE:

3 courses will run in parallel during the whole event. Participants will be able to freely choose the courses they wish to attend as well as to move from one to another.

All lectures will be videorecorded. Participants will be able to watch them again for 45 days after the event.

An open session will give participants the opportunity to present their own work in progress in 5 minutes. Also companies will be able to present their technical developments for 10 minutes.

The school will include a hackathon, where participants will be able to work in teams to tackle several machine learning challenges.

Full live online participation will be possible. The organizers highlight, however, the importance of face to face interaction and networking in this kind of research training event.

KEYNOTE SPEAKERS:

Yonina Eldar (Weizmann institute of Science), Model Based Deep Learning: Applications to Imaging and Communications

Manuela Veloso (JPMorganChase), The Journey of Humans and AI: Insights from AI in Robotics and AI in Finance

PROFESSORS AND COURSES:

Pierre Baldi (University of California Irvine), [intermediate/advanced] From Deep Learning and Transformers to AI Risks and Safety

Sean Benson (Amsterdam University Medical Center), [intermediate] Digital Twins and Generative AI for Personalised Medicine

Xavier Bresson (National University of Singapore), [intermediate/advanced] Graph Transformers, Graph Generative Models and Large Language Models

Nello Cristianini (University of Bath), [introductory] Toward Ever More Clever Machines: The Evolution and Future of AI

Mark Derdzinski (Dexcom), [introductory] From Prototype to Production: Evaluation Strategies for Agentic Applications

Samira Ebrahimi Kahou (University of Calgary), [intermediate/advanced] Explainability in Machine Learning

Elena Giusarma (Michigan Technological University), [introductory/intermediate] Machine Learning at the Frontier of Astrophysics: Simulating the Universe

Shih-Chieh Hsu (University of Washington), [intermediate/advanced] Real-Time Artificial Intelligence for Science and Engineering

Xia “Ben” Hu (Rice University), [introductory/advanced] Efficient LLM Serving: Algorithms and Systems

Lu Jiang (ByteDance & Carnegie Mellon University), [introductory/intermediate] Transformers for Image and Video Generation: Fundamentals, Design, and Innovations

Jayashree Kalpathy-Cramer (University of Colorado), [introductory/intermediate] Multimodal AI for Healthcare

Yingbin Liang (Ohio State University), [intermediate/advanced] Theory on Training Dynamics of Transformers

Chen Change Loy (Nanyang Technological University), [intermediate/advanced] Harnessing Prior for Content Enhancement and Creation

Fenglong Ma (Pennsylvania State University) & Cao (Danica) Xiao (GE HealthCare), [introductory/intermediate] Transforming Healthcare and Drug Development through Multimodal AI with LLMs and Generative AI Technologies

Evan Shelhamer (DeepMind), [intermediate] Test-Time Adaptation for Updating on New and Different Data

Atlas Wang (University of Texas Austin), [intermediate] Low Rank Strikes Back in the Era of Large Language Models

Xiang Wang (University of Science and Technology of China), [advanced] Large Language Models for User Behavior Modeling: Cross-Modal Interpretation, Preference Optimization, and Agentic Simulation

Rex Ying (Yale University), [intermediate/advanced] Multimodal Foundation Models for Graph-Structured Data: Framework and Scientific Applications

OPEN SESSION:

An open session will collect 5-minute voluntary oral presentations of work in progress by participants.

They should submit a half-page abstract containing the title, authors, and summary of the research to david@irdta.eu by July 13, 2025.

INDUSTRIAL SESSION:

A session will be devoted to 10-minute demonstrations of practical applications of deep learning in industry.

Companies interested in contributing are welcome to submit a 1-page abstract containing the program of the demonstration and the logistics needed. People in charge of the demonstration must register for the event.

Expressions of interest have to be submitted to david@irdta.eu by July 13, 2025.

HACKATHON:

A hackathon will take place, where participants can work in teams to tackle several machine learning challenges. They will be coordinated by Professor Sergei V. Gleyzer (University of Alabama). The challenges will be released 2 weeks before the beginning of the school. A jury will judge the submissions and the winners of each challenge will be announced by August 25, 2025. The winning teams will receive a modest monetary prize and the runners-up will get a certificate.

SPONSORS:

Companies/institutions/organizations willing to be sponsors of the event can download the sponsorship leaflet from

ORGANIZING COMMITTEE:

Samuel Anjos (Maia, social networks)
Sergei V. Gleyzer (Tuscaloosa, hackathon chair)
José Paulo Marques dos Santos (Maia, local chair)
Carlos Martín-Vide (Tarragona, program chair)
Santiago Montes (Tarragona, webpage)
Sara Morales (Luxembourg)
José Luís Reis (Maia)
Luís Paulo Reis (Porto)
David Silva (London, organization chair)

REGISTRATION:

It has to be done at

The selection of 6 courses requested in the registration template is only tentative and non-binding. For logistical reasons, it will be helpful to have an estimation of the respective demand for each course.

Since the capacity of the venue is limited, registration requests will be processed on a first come first served basis. The registration period will be closed and the on-line registration tool disabled when the capacity of the venue will have got exhausted. It is highly recommended to register prior to the event.

FEES:

Fees comprise access to all program activities and lunches.

There are several early registration deadlines. Fees depend on the registration deadline.

The fees for on site and for online participation are the same.

ACCOMMODATION:

Accommodation suggestions are available at

CERTIFICATE:

A certificate of successful participation in the event will be delivered indicating the number of hours of academic activities. This should be sufficient for those participants who plan to request ECTS recognition from their home university.

QUESTIONS AND FURTHER INFORMATION:

ACKNOWLEDGMENTS:

Universidade da Maia

Universidade do Porto

Universitat Rovira i Virgili

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CfP: Workshop on Alternative Visual Domains for Detection, Tracking and Forecasting @ ICIAP2025

June 24th, 2025 Daniela Lopez de Luise
===================================================
Call for papers – Apologies for multiple posting
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AVD 2025 – Alternative Visual Domains for Detection, Tracking and Forecasting – @ICIAP 2025
Held in conjunction with the 23nd International Conference on Image Analysis and Processing (ICIAP) – September 15-16, 2025, Rome (Italy)
===================================================
The perception and understanding of dynamic environments rely heavily on visual data, which has traditionally been captured using RGB cameras. However, alternative visual domains-such as thermal imaging, event-based cameras, LiDAR, hyperspectral sensors, and radar-offer new opportunities and challenges in detection, tracking, and forecasting tasks. These unconventional modalities provide valuable advantages in scenarios where standard RGB-based approaches struggle, such as low-light conditions, adverse weather, and high-speed motion analysis.
The complexity and diversity of these data sources require the development of specialized processing techniques, often involving novel Deep Learning methodologies. Event-based cameras, for instance, capture asynchronous intensity changes at a microsecond scale, enabling ultra-low-latency motion tracking. Thermal imaging can enhance pedestrian detection in nighttime conditions, while LiDAR and radar enable accurate distance estimation for autonomous systems. Additionally, hyperspectral imaging can extract material properties beyond what standard cameras perceive, contributing to applications in medical diagnostics, agriculture, and security.
Despite their advantages, alternative visual sensors introduce unique challenges, including domain adaptation, sensor fusion, and real-time processing constraints. As industries increasingly integrate these technologies into safety-critical applications – such as autonomous driving, industrial inspection, and environmental monitoring-there is a growing demand for efficient and robust models capable of handling multi-modal data streams.
This workshop aims to foster collaboration between researchers and industry practitioners, encouraging the exchange of ideas on novel sensing modalities, algorithmic advancements, and real-world applications. Furthermore, the ethical and privacy implications of these alternative visual domains will be explored, addressing concerns related to surveillance, biometric recognition, and data security.
===================================================
TOPICS
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Human and Object Perception
Multi-Sensor People Detection and Tracking
2D/3D Pose Estimation from Alternative Modalities (e.g., Thermal, LiDAR, Event Cameras)
Gait Analysis and Re-identification in Non-RGB Domains
Action and Gesture Recognition with Event-based and Depth Sensors
Anthropometric Measurements from Multi-Spectral and Depth Data
3D Body Reconstruction from LiDAR and Infrared
First-Person Vision Using Event Cameras and/or Thermal Sensors
Face and Head Analysis
Facial Landmarks and Head Pose Estimation in Thermal and Near-Infrared Images
Facial Expression and Emotion Recognition Beyond RGB
Identity Recognition with Multi-Spectral and Hyperspectral Imaging
Object and Scene Understanding
Thermal and Radar-based Object and Person Detection
LiDAR and Event-Based Tracking in Dynamic Environments
Scene Parsing and Semantic Segmentation from Non-Visible Spectrum Sensors
Multi-Modal Perception and Synthesis
Sensor Fusion for Detection, Tracking, and Forecasting
Multi-Spectral and Event-based Image and Video Synthesis
Generative Models for Data Enhancement in Alternative Domains
Privacy, Fairness, and Computational Challenges
Novel Datasets Leveraging Alternative Visual Domains
Bias and Fairness in Non-RGB Perception Systems
Privacy-Preserving Approaches for Multi-Sensor Data
Real-Time and Embedded Processing for Alternative Visual Sensors
Biometric and Security Applications
Face and Gait Recognition in Non-RGB Modalities
Fingerprint and Iris Recognition with Infrared and Multi-Spectral Imaging
Spoofing and Attack Detection in Thermal and Depth-Based Biometrics
Fast Moving Objects Detection and Tracking
Motion Blur Reduction in High-Velocity Scenarios Using Alternative Modalities
Real-Time Tracking of Fast-Moving Objects in Low-Light and Adverse Conditions
Multi-Sensor Fusion for High-Speed Object Perception
Ultra-Low Latency Tracking with Event Cameras and Radar
Domain Adaptation for Fast-Moving Object Recognition Across Modalities
Autonomous Driving Perception and Forecasting
Scenario-based Motion Forecasting
3D Scene Understanding and Semantic Segmentation
Event and LiDAR-Based Object Detection and Tracking
Optical Flow and Depth Estimation for Ego-Motion Perception
Ultra-Low Latency Sensor Processing for Real-Time Decision Making
=================
IMPORTANT DATES
=================
Paper Submission Deadline: 27/06/2025
Decision to Authors: 04/07/2025
Camera ready papers due: 08/07/2025
Workshop date: September 15-16
======================
SUBMISSION GUIDELINES
======================
All the papers should be submitted at: https://cmt3.research.microsoft.com/AVD2025
The maximum number of pages is 12 pages including references. While preparing their contributions,
authors must follow guidelines and technical instructions provided by Springer that can be found at:
Papers will be selected through a double-blind review process, taking into account originality,
significance, clarity, soundness, relevance and technical contents.
Each accepted paper must be covered by at least one registered author.
====================
WORKSHOP MODALITY
====================
The workshop will be held in conjunction with the International Conference on Image Analysis and Processing (ICIAP 2025).
======================
ORGANIZING COMMITTEE
======================
Federico Becattini, University of Siena, Italy – federico.becattini@unisi.it
Francesco Marchetti, University of Florence, Italy – francesco.marchetti@unifi.it
Lorenzo Berlincioni, University of Florence, Italy – lorenzo.berlincioni@unifi.it
Gabriele Magrini, University of Florence, Italy – gabriele.magrini@unifi.it
Università di Siena
Federico Becattini
Dipartimento di ingegneria dell'informazione e scienze matematiche
Tenure Track Assistant Professor (RTD-B)
Università di Siena

Via Roma, 56 (room 121)

53100 Siena | Italy

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