7059 research outputs found
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Public and Private in the Law of Public Nuisance
No full textLecture by Arthur Ripstein (University of Toronto, Canada) on the public and private aspects of "public nuisance" lawConferència a càrrec d'Arthur Ripstein, de la Universitat de Torornto, Canadà sobre els aspectes públic i privat en la llei de les "molèsties públiques"7694.mp4
7694.mp
MapICGC GL JS: una nueva librería open source para la visualización de vector tiles y 3D tiles
No full textLucia Struth oferiex una conferència dins el marc de les 17enes Jornades de SIG Lliure 2024 organitzades pel SIGTE de la Universitat de Girona sobre MapICGC GL JS que s’ha desenvolupat amb l’objectiu de millorar les capacitats de cartografia web i proporcionar als programadors web una solució integrada i de fàcil accés a les dades pròpies de l’Institut Cartogràfic i Geològic de Catalunya (ICGC). La biblioteca incorpora una sèrie de pràctiques funcionalitats i integra fàcilment elements de l’ICGC com ara imatges satel·litàries històriques, elements vectorials (FlatGeobuf) i models 3D hiperrealistes. A més, inclou un nou geocodificador amb cerques complexes. MAPICGC GL JS és un exemple de biblioteca de codi obert aplicable tant dins com fora de l’ICGC7643.mp4
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First set of communications presented at "2024 Symposium Tort Law Reform in Europe and Beyond: Why is Tort Law Reform so Difficult?"
No full textPrimer bloc de comunicacions presentades al "2024 Symposium Tort Law Reform in Europe and Beyond: Why is Tort Law Reform so Difficult?" sobre la reforma de la Llei de Danys a diferents llocs d'Europa, Sudàfrica, Xile, Turquia, i Portugal, a càrrec d'Emile Zitzke (University of the Witwatersrand, Johannesburg), Ignacio Ríos (Universitat de Xile), Rui Cascao (Universitat de Coimbra), Réka Pusztahelyi (Universitat de Miskolc, Hongria), Stefano Gatti (Universitat de Verona, Itàlia), Kaan Can Yildirim (Universitat de Kadir Has, Turquia), Alician Caliskan (Universitat de Varsòvia), Witold Borysiak (Universitat de Varsòvia), Andrea Parziale (Universitat de Maastricht, Països Baixos) i Hélène Guiziou (Universitat de Paris 2)Reforma de la Llei de danys7689.mp4
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Second set of communications presented at "2024 Symposium Tort Law Reform in Europe and Beyond: Why is Tort Law Reform so Difficult?"
No full textSegon bloc de comunicacions presentades al "2024 Symposium Tort Law Reform in Europe and Beyond: Why is Tort Law Reform so Difficult?" sobre la reforma de la Llei de Danys a diferents llocs, a càrrec de Gabriel Settler, Bruna de Souza Moulin Alcântara da Silva (Universidade Federal do Espírito Santo, Brasil), Yoni Bosschaart (Universitat Erasmus de Rotterdam), Pedro del Olmo Garcia (Universitat Carlos III de Madrid) i Fuglinszky Ádám (Universitat Eötvös Loránd, Budapest)7692.mp4
7692.mp
10th Living Knowledge Conference 2024: sessió plenària 2
No full textSecond plenary session of the "10th Living Knowledge Conference 2024", moderated by Réka Matolay. Presentations by Valentina C.Tassone, entitled "Curriculum engagement in times of crisis: who are we engaging with and for what purpose?"; Catherine O'Mahoney talks about civic behavior in higher education and Karel Proot, presents the communication entitled "Student-Led Summer: learning for the crisis in community"Segona sessió plenària de la "10th Living Knowledge Conference 2024", moderada per Réka Matolay. Presentacions de Valentina C.Tassone, titulada " Curriculum engagement in times of crisis: who are we engaging with and for what purpose?"; Catherine O'Mahoney parla sobre el comportament cívic en l'educació superior i Karel Proot, presenta la comunicació titulada "Student-Led Summer: learning for the crisis in community"7677.mp4
7677.mp
Opening: CP 2024. The 30th International Conference on Principles and Practice of Constraint Programming
No full textPresentació de la Conferència Internacional sobre Principis i Pràctica de la Programació de Restriccions (CP), que és la principal conferència anual sobre tots els aspectes de la informàtica amb restriccions, incloent teoria, algorismes, models, solucionadors i una àmplia gamma d'aplicacions en aprenentatge automàtic/intel·ligència artificial , planificació i programació, per citar-ne alguns. Aquesta és la 30a versió de la sèrie CP organitzada per l'Associació per a la Programació de Restriccions.
El programa CP 2024 inclourà presentacions d'articles científics d'alta qualitat sobre tecnologia de restriccions, amb múltiples temes. Estarà ubicat a l'antiga ciutat de Girona, a les dependències del campus del nucli antic de la Universitat de GironaPresentation of the International Conference on Principles and Practice of Constraint Programming (CP) that is the premier annual conference on all aspects of computing with constraints, including theory, algorithms, models, solvers, and a diverse range of applications in machine learning/artificial intelligence, planning, and scheduling, to name a few. This is the 30th version of the CP series organized by the Association for Constraint Programming.
The CP 2024 program will include presentations of high quality scientific papers on constraints technology, featuring multiple thematic tracks. It will be located in the ancient city of Girona, at the premises of the old town campus of the University of Girona7726.mp4
7726.mp
Slide&Drill, a new Approach for Multi-Objective Combinatorial Optimization
No full textJoao Cortes, from INESC ID, from Lisboa, tells about the successful use of Propositional Satisfiability (SAT) algorithms in Boolean optimization (e.g., Maximum Satisfiability), several SAT-based algorithms have been proposed for Multi-Objective Combinatorial Optimization (MOCO). However, these new algorithms either provide a small subset of the Pareto front or follow a more exploratory search procedure and the solutions found are usually distant from the Pareto front. We extend the state of the art with a new SAT-based MOCO solver, Slide and Drill (Slide&Drill), that hones an upper bound set of the exact solution. Moreover, we show that Slide&Drill neatly complements proposed UNSAT-SAT algorithms for MOCO. These algorithms can work in tandem over the same shared “blackboard” formula, in order to enable a faster convergence. Experimental results in several sets of benchmark instances show that Slide&Drill can outperform other SAT-based algorithms for MOCO, in particular when paired with previously proposed UNSAT-SAT algorithms7730.mp4
7730.mp
Doctoral Research Award. Scalability in Decision-Focused Learning: State of the Art, Challenges, and Beyond
No full textThis presentation will explore recent advancements in Decision-Focused Learning (DFL), an emerging approach in artificial intelligence (AI) that integrates machine learning (ML) prediction with combinatorial optimization to train ML models for optimal decision-making. DFL predicts the unknown parameters of combinatorial optimization problems by focusing on the outcomes obtained using these predicted parameters. This presentation will start by providing an overview of various DFL techniques and introduce a taxonomy that categorizes these methods based on their distinct features. It will then highlight the scalability challenge, a major bottleneck for real-world DFL applications. The presentation will summarize existing strategies developed to address this issue and conclude by exploring potential future directions in the field7760.mp4
7760.mp
Combining Constraint Programming Reasoning with Large Language Model Predictions
No full textConstraint Programming (CP) and Machine Learning (ML) face challenges in text generation due to CP's struggle with implementing "meaning" and ML's difficulty with structural constraints. This paper proposes a solution by combining both approaches and embedding a Large Language Model (LLM) in CP. The LLM handles word generation and meaning, while CP manages structural constraints. This approach builds on On-the-fly Constraint Programming Search (OTFS), improving it using LLM-generated domains. Compared to Beam Search (BS), a standard NLP method, this combined approach (OTFS with LLM) is faster and produces better results, ensuring all constraints are satisfied. This fusion of CP and ML presents new possibilities for enhancing text generation under constraints7763.mp4
7763.mp
Constraint Modelling with LLMs using In-Context Learning
No full textKostis Michailidis from KU Leuven in Belgium, tells that the Constraint Programming (CP) allows for the modelling and solving of a wide range of combinatorial problems. However, modelling such problems using constraints over decision variables still requires significant expertise, both in conceptual thinking and syntactic use of modelling languages. In this paper, we explore the potential of using pre-trained Large Language Models (LLMs) as coding assistants, to transform textual problem descriptions into concrete and executable CP specifications. We investigate different transformation pipelines with explicit intermediate representations, and we investigate the potential benefit of various retrieval-augmented example selection strategies for in-context learning. We evaluate our approach on 2 datasets from the literature, namely NL4Opt (optimisation) and Logic Grid Puzzles (satisfaction), and on a heterogeneous set of exercises from a CP course. The results show that pre-trained LLMs have promising potential for initialising the modelling process, with retrieval-augmented in-context learning significantly enhancing their modelling capabilities7764.mp4
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