fca-list April 2025

fca-list@cs.uni-kassel.de

3 participants
3 discussions

[CFP] Foundations and Future of Change in Artificial Intelligence (FCAI) - Workshop @ ECAI

by Kai Sauerwald

**************************************************************************************** FCAI 2025 @ ECAI 2025 Foundations and Future of Change in Artificial Intelligence October 25/26, Bologna, Italy https://fcai2025.machine-reasoning.org/ Workshop co-located with the 28th European Conference on Artificial Intelligence (ECAI 2025) **************************************************************************************** Changing information transversely affects nearly any task and process that we aim to formalize computationally. Consequently, making sense of how to change information is a central aspect and precursor for further advancements in many domains. Naturally, approaches to describe changes, to deal with change, and to conduct changes have been developed in very different areas of artificial intelligence. These approaches generally consider changing from different angles and highlight diverse aspects that sometimes complement each other. For instance, in database theory, much work has been devoted to transactions as the main representation of change and the study of how that affects the computational complexity of querying such databases. On the other hand, researchers in belief change investigated the axiomatic and semantics of different kinds of changes in formal theories. Recent advancements in Machine Learning pose new and exciting challenges in formal approaches to change, which seem conceptually different from classical approaches to change. This workshop aims to bring together researchers from different areas of AI and beyond who work on change in their respective areas and see potential in bridging approaches or for radically advanced existing approaches to change to be combined with new ideas and perspectives. We also invite works that provide general insights on change that are important for multiple areas of artificial intelligence or even for computer science in general. ********************** *** List of Topics *** The workshop welcomes contributions on every topic related to the formal treatment of change, the evolution of representations in artificial intelligence, and approaches that implement such approaches. The following lists potential topics (but is not limited to these): • Position papers on the foundations and future of change • Logics for the representations of changes or reasoning about changes • Belief change theory • Repair in databases and ontologies • Database update and querying • Dynamic complexity theory • Approaches to the meaning and semantics of change, e.g., conditionals and plausibility • Alternative meanings of change • Theories of aspects and kinds of changes, like inconsistency, time or ontologies of change • Foundations of editing, retraining or learning of subsymbolic representations • Learning as a change process • Algorithms to compute changes • Approaches to track changes • Philosophical aspects of change • Updating incomplete information • Dynamics of logic and database systems • Evolution and versioning • Reasoning about update programs ******************************** *** Deadlines and Submission *** • Paper submission: July 13, 2025 • Notification: August 3, 2025 • Workshop: October 25/26, 2025 (tentative) There are two types of submissions: • Full papers. Full papers should be at most 18 pages (one column), excluding references and acknowledgments. Papers already published or accepted for publication at other conferences are also welcome, provided that the original publication is mentioned in a footnote on the first page and the submission at FCAI falls within the authors’ rights. In the same vein, papers under review for other conferences can be submitted with a similar indication on their front page. • Extended Abstracts. Extended abstracts should be at most 5 pages (one column), excluding references and acknowledgments. The abstracts should introduce work that has recently been published, is under review, or is ongoing research at an advanced stage. We highly encourage to attach to the submission a preprint/postprint or a technical report. Such extra material will be read at the discretion of the reviewers. Submitting already published material may require permission by the copyright holder. Submission will be through the EasyChair conference system: https://easychair.org/my/conference?conf=fcai2025 The accepted papers will be made available electronically in the CEUR Workshop Proceedings series as informal proceedings (http://ceur-ws.org/). The copyright of the papers remains with the authors. Full papers will be indexed by dblp.org; but extended abstracts published on CEUR proceedings will not be indexed by dblp.org. ***************** *** PC Chairs *** • Maria Vanina Martinez (Artificial Intelligence Research Institute (AAAI-CSIC), Barcelona, Spain) • Nina Pardal (University of Huddersfield, UK) • Kai Sauerwald (FernUniversität in Hagen, Germany) *************************** *** Further Information *** For further information, please visit the FCAI webpage: https://fcai2025.machine-reasoning.org/ Please feel free to contact the organizer of FCAI 2025. Information on the venue and registration can be obtained from the ECAI 2025 website: https://ecai2025.org/

2 weeks, 1 day

107. Arbeitstagung Allgemeine Algebra (AAA107) [107th Workshop on General Algebra] (second announcement)

by Leonard Kwuida

107. Arbeitstagung Allgemeine Algebra (AAA107) [107th Workshop on General Algebra] www.bfh.ch/aaa107 *June 20-22, 2025* preceded by mini-courses on CSP and Quantum Computing, *June 18--20, 2025* The AAA107 is jointly organized by the University of Bern, the Bern University of Applied Sciences (BFH) and the Pädagogische Hochschule Bern. It is coordinated by the BFH and will take place on the Marzili campus of School of Business, Bern University of Applied Sciences, Brückenstrasse 73, 3005, Bern, Switzerland. The scientific program starts on Friday, 20 June 2025 at 9:00, and ends on Sunday, 22 June 2025 at 13:00. In addition, AAA107 will feature two mini-courses (June 18--20 2025) and an application session (Friday June 20th 2025). *Plenary lectures*: - David Clark (SUNY New Paltz, USA). Title: Groupoid Terms from Biological Evolution - Mai Gehrke (Université Côte D’Azur, France). Title: A unifying point of view on various topological dualities for lattices - Gergő Gyenizse (University of Szeged, Hungary). Title: Strongly abelian subsets - George Metcalfe (Universität Bern, Switzerland). Title: Equational reasoning in ordered groups and ordered monoids - Jakub Opršal (University of Birmingham, UK). - Serafina Lapenta (University of Salerno, Italy). Title: Baker-Beynon duality beyond semisimplicity. - Hanamantagouda P. Sankappanavar (SUNY New Paltz, USA). - Etienne Temgoua A. (University of Yaoundé I, Cameroon). Title: Double Boolean Algebras. *Contributed Talks*: Besides the plenary talks, contributed talks by the conference participants will be scheduled. If you intend to give a contributed talk (25min), please register and submit an abstract not later than 31st May 2025. *Mini courses*: June 18—20, 2025 - A mini-course on Constraint Satisfaction Problem (led by Dmitriy Zhuk, Charles University, Czech Republic) - A mini course on Quantum Computing (led by Stefan Wolf, Università della Svizzera italiana) *Application Session* On Friday 20th June 2025, there will be an open session for everybody on Applications of Algebra: a Rubik's Cube contest (led by Leonard Kemachin, Gymnasium Kirchenfeld, Bern), followed by a gentle introduction to the abstract algebra behind it (led by Peter Mayr, University of Colorado at Boulder, USA) *Organization Committee*: Joel Adler (PH Bern), Isabel Hortelano Martín (Uni Bern), Adam Kurpisz (BFH), Michel Krebs (BFH, co-chair), Leonard Kwuida (BFH, co-chair) Reinhard Riedl (BFH), Simon Santschi (Uni Bern). Prof. Dr. Leonard Kwuida Dozent für Mathematik, Statistik und Data Science https://sites.google.com/view/kwuida <https://sites.google.com/view/kwuida/home>

2 weeks, 5 days

XVII Madrid UPM Machine Learning and Advanced Statistics Summer School (June 16th - June 27th, 2025) - Early registration reminder

by mlas＠fi.upm.es

Dear colleagues, We would like to remind you that early registration for the Madrid UPM Machine Learning and Advanced Statistics summer school is open until May, 27th (included). The summer school will be held in Boadilla del Monte, near Madrid, from June 16th to June 27th. This year's edition comprises 12 week-long courses (15 lecture hours each), given during two weeks (six courses each week). Attendees may register in each course independently. No restrictions, besides those imposed by timetables, apply on the number or choice of courses. Early registration is *OPEN*. Extended information on course programmes, price, venue, accommodation and transport is available at the school's website: https://www.dia.fi.upm.es/MLAS There is a 25% discount for members of Spanish AEPIA and SEIO societies. Please, forward this information to your colleagues, students, and whomever you think may find it interesting. Best regards, Pedro Larrañaga, Concha Bielza, Bojan Mihaljević and Laura Gonzalez Veiga. -- School coordinators. *** List of courses and brief description *** # Week 1 (June 16th - June 20th, 2025) ## 1st session: 9:45-12:45 ### Course 1: Bayesian Networks (15 h) Basics of Bayesian networks. Inference in Bayesian networks. Learning Bayesian networks from data. Real applications. Practical demonstration: R. ### Course 2: Time Series(15 h) Basic concepts in time series. Linear models for time series. Time series clustering. Practical demonstration: R. ## 2nd session: 13:45-16:45 ### Course 3: Supervised Classification (15 h) Introduction. Assessing the performance of supervised classification algorithms. Preprocessing. Classification techniques. Combining multiple classifiers. Comparing supervised classification algorithms. Practical demonstration: python. ### Course 4: Reinforcement learning (15 h) Introduction. Dynamic programming methods. Temporal-difference learning. Policy gradient methods. Causal reinforcement learning. Practical demonstration: R. ## 3rd session: 17:00 - 20:00 ### Course 5: Deep Learning (15 h) Introduction. Learning algorithms. Learning in deep networks. Deep Learning for Computer Vision. Deep Learning for Language. Practical session: Python notebooks with Google Colab with keras, Pytorch and Hugging Face Transformers. ### Course 6: Bayesian Inference (15 h) Introduction: Bayesian basics. Conjugate models. MCMC and other simulation methods. Regression and Hierarchical models. Model selection. Practical demonstration: R and WinBugs. # Week 2 (June 23rd - June 27th, 2025) ## 1st session: 9:45-12:45 ### Course 7: Causality (15 h) Introduction. Causal graphs. Mediation analysis. Sensitivity analysis to unmeasured confounding. Counterfactual reasoning. Practical sessions: R. ### Course 8: Clustering (15 h) Introduction to clustering. Data exploration and preparation. Prototype-based clustering. Density-based clustering. Graph-based clustering. Cluster evaluation. Miscellanea. Conclusions and final advice. Practical session: R. ## 2nd session: 13:45-16:45 ### Course 9: Gaussian Processes and Bayesian Optimization (15 h) Introduction to Gaussian processes. Sparse Gaussian processes. Deep Gaussian processes. Introduction to Bayesian optimization. Bayesian optimization in complex scenarios. Practical demonstration: python using GPytorch and BOTorch. ### Course 10: Explainable Machine Learning (15 h) Introduction. Inherently interpretable models. Post-hoc interpretation of black box models. Basics of causal inference. Beyond tabular and i.i.d. data. Other topics. Practical demonstration: Python with Google Colab. ## 3rd session: 17:00-20:00 ### Course 11: Generative AI (15 h) Introduction to the course. Neural networks and deep learning. Generative AI for images. Generative AI for language. Hands-on session: Pytorch, VAEs, GANs, diffusion models, LLMs, aligning a generative LLM, using an open-source image generation model. ### Course 12: Feature Subset Selection (15 h) Introduction. Filter approaches. Embedded methods. Wrapper methods. Additional topics. Hands-on sessions: R and python.

2 weeks, 6 days

2025

2024

2023

2022

2021

fca-list April 2025