Seminari - Dipartimento Informatica validi dal 26.04.2024 al 26.04.2025. https://www.di.univr.it/?ent=seminario&rss=0 https://www.di.univr.it/?ent=seminario&rss=0&id=6266 Relatore: Thiago D. Simão; Provenienza: Eindhoven University of Technology; Data inizio: 2024-05-29; Ora inizio: 12.30; Referente interno: Alberto Castellini; Riassunto: Safety is a crucial concern when deploying reinforcement learning (RL) algorithms in real-world scenarios. In this two-part lecture series, we delve into safety considerations from two perspectives: ensuring reasonable performance and adhering to predefined constraints. - PART 1. In the first segment, we investigate the offline setting where the RL agent solely accesses a fixed dataset of prior trajectories, devoid of direct interaction with the environment. Given the availability of the behavior policy responsible for data collection, the primary challenge is crafting a policy that outperforms such behavior policy. We study algorithms that leverage the behavior policy to compute an improved policy with high probability and discuss how to improve their sample efficiency. - PART 2. Transitioning to the latter segment, we confront the limitations inherent in specifying the behavior expected from an agent solely via a reward function. We introduce a model that mitigates this issue using constraints, and we discuss how to compute the corresponding optimal policy when the problem is known. Finally, we study algorithms that can efficiently explore the environment and eventually converge to an optimal policy when the model is unknown. Schedule: May 29, 12.30-14.30 (Room B) May 29, 15.30-17.30 (Room 1.02) May 31, 15.30-17.30 (Room 1.02) June 5, 12.30-14.30 (Room B) June 5, 15.30-17.30 (Room 1.02 June 7, 15.30-17.30 (Room 1.02) The minicourse is related to the quot;Reinforcement Learningquot; course (Master in Artificial Intelligence). Wed, 29 May 2024 12:30:00 +0200 https://www.di.univr.it/?ent=seminario&rss=0&id=6266 https://www.di.univr.it/?ent=seminario&rss=0&id=6279 Relatore: Riccardo Volpi; Provenienza: Naver Labs Europe - France; Data inizio: 2024-05-28; Ora inizio: 14.00; Note orario: Sala Verde; Referente interno: Vittorio Murino; Riassunto: In definizione. Tue, 28 May 2024 14:00:00 +0200 https://www.di.univr.it/?ent=seminario&rss=0&id=6279 https://www.di.univr.it/?ent=seminario&rss=0&id=6285 Relatore: Valentina Mazzi; Provenienza: Politecnico di Torino; Data inizio: 2024-05-20; Ora inizio: 10.30; Referente interno: Giacomo Albi; Riassunto: Abstract: Recent advances in medical imaging, modeling , and Computational Fluid Dynamics (CFD) have allowed the modeling of local blood flow patterns in realistic, personalized vascular districts aiming at (1) improving the current understanding of the role played by the local hemodynamics in vascular pathophysiology, and in a wider perspective (2) demonstrating how some clinical information can be derived from computational simulations. This mini course will offer an in depth overview of the real world applications of mathematical techniques to investigate the intricate mechanisms governing blood flows within the human cardiovascular system e xplor ing the clinical applications of cardiovascular flow dynamics in diagnosing and managing cardiovascular diseases , ultimately improving patient outcomes. Schedule: Monday 20 May, 10:30 - 12:30. Aula G Thursday 23 May,10:30 - 13:30. Aula G Tuesday 28 May, 10:30 -13:30. Aula G Thursday 30 May, 10:30 - 12:30. Aula G . Mon, 20 May 2024 10:30:00 +0200 https://www.di.univr.it/?ent=seminario&rss=0&id=6285 https://www.di.univr.it/?ent=seminario&rss=0&id=6070 Relatore: Silvia Lavagnini; Provenienza: Oslo University - Department of Data Science and Analytics Nydalsveien; Data inizio: 2024-05-13; Referente interno: Luca Di Persio; Riassunto: In this mini-course we will discuss various numerical methods for the pricing of financial instruments, with a particular focus on applications to the energy markets. We will start from the simulations of some of the most common continuous-time models, such as the geometric Brownian motion and the Ornstein-Uhlenbeck process. Stochastic volatility models, such as the Heston model, may also be discussed. We will then consider different approaches for options pricing, such as the PDE and the Monte Carlo approach. State-dependent options may also be discussed. Finally, forward contracts with delivery period typical of the energy markets will be treated from the Heath-Jarrow-Morton modelling point of view. If time allows, we will also discuss (simulations of) SPDEs for Hilbert space-valued forward curves. The course will be given in Python. Mon, 13 May 2024 00:00:00 +0200 https://www.di.univr.it/?ent=seminario&rss=0&id=6070 https://www.di.univr.it/?ent=seminario&rss=0&id=6256 Relatore: Daniela Bubboloni; Provenienza: Università di Firenze; Data inizio: 2024-05-09; Ora inizio: 15.30; Note orario: Aula L (presenza e remoto); Referente interno: Lidia Angeleri; Riassunto: Da definire Link:_https://unipd.zoom.us/j/82518660070?pwd=RUpxL1FnZG9yVzFrOCtrM0xYMEZaZz09_ Meeting ID: 825 1866 0070 Password: 62542 Referente: Lidia Angeleri . Thu, 9 May 2024 15:30:00 +0200 https://www.di.univr.it/?ent=seminario&rss=0&id=6256 https://www.di.univr.it/?ent=seminario&rss=0&id=6284 Relatore: Vincenzo Manca; Provenienza: Professore onorario Università di Verona; Data inizio: 2024-05-07; Ora inizio: 10.00; Note orario: Aula H (solo in presenza); Referente interno: Giuditta Franco; Riassunto: Abstract: Recently, Large Language Models (LLM) have shown the cruciality of natural language in learning and developing complex artificial intelligent behaviors. The seminar presents an agile method of logical semantics based on high-order Monadic Predicate Logic (HML). An operator of predicate abstraction is introduced that provides a simple mechanism for logical aggregation of predicates and logical typing. Monadic high-order logic is the natural environment in which predicate abstraction expresses the semantics of typical linguistic structures. Many examples of logical representations of natural language sentences in HLL (HML+NL) are provided. Finally, network models, extensions, and applications for the interaction with chatbots are briefly discussed (Main Reference: V. Manca, ldquo;Agile Logical Semantics for Natural Languagesrdquo;, Information, Vol. 15, Issue 1, 64; 2024). CV: Vincenzo Manca studied Mathematics at the University of Pisa, under the supervision of Alfonso Caracciolo (ICNR) and Ennio De Giorgi (Scuola Normale Superiore). He worked and taught at the universities of Pisa, Udine, Limerick, and Verona, where he was a full professor of Computer Science (2002-2019). He developed research in Mathematical Logic, Formal Languages, Computability, Information Theory, Mathematical Linguistics, and Bioinformatics. He published more than 200 journal papers and 20 books, being also a member of the editorial board of various international scientific journals and about 30 international conferences. He directed research projects by collaborating with groups in Europe, USA, China, and Japan. In 2006 he cofounded the bachelor course in Bioinformatics and in 2016 the master coure in Medical Bioinformatics, at the University of Verona, where, in 2008, he cofounded the Museum of History of Computer Science and became the director of CBMC (Center di BioMedical Computing). A special issue of ldquo;Natural Computingrdquo; (Springer, March 2011) was dedicated to him. Since 2019 he is an Honorary Professor of Computer Science at the University o. Tue, 7 May 2024 10:00:00 +0200 https://www.di.univr.it/?ent=seminario&rss=0&id=6284 https://www.di.univr.it/?ent=seminario&rss=0&id=6276 Relatore: Franco Zivcovich; Provenienza: Neurodec, Nice, France; Data inizio: 2024-05-06; Ora inizio: 12.30; Note orario: starting date; Referente interno: Marco Caliari; Riassunto: In this course you will gain a deep understanding of Finite Element Methods (FEM) using Python. We will start by revisiting sparse data structures and iterative solvers, utilizing popular libraries like Numpy, Scipy, and high-performance packages such as PETSc. You will then delve into unstructured simplicial meshes, learn to work within the reference element, and employ meshes for approximating integrals over complex domains. Furthermore, you will develop expertise in piecewise approximation and master the assembly of matrices crucial in solving Partial Differential Equations (PDEs) with Finite Elements. By completing this course, you will not only grasp the mechanics of FEM at an unparalleled depth but also acquire the skills to tailor specific solutions for unique engineering problems. This knowledge will set you apart from engineers who rely solely on off-the-shelf, compiled packages like FEniCS and FreeFEM++, allowing you to achieve unmatched performance in your engineering endeavors. Join us in this course and embark on a journey to become a proficient engineer capable of navigating the complex world of mathematical modeling and computational engineering. Timetable: May 6, 12:30-14:30, room G May 8, 9:30-11:30, meeting room second floor May 9, 9:30-11:30, room L May 20, 12:30-14:30, room G May 22, 16:30-18:30, room L May 23, 9:30-11:30, room L . Mon, 6 May 2024 12:30:00 +0200 https://www.di.univr.it/?ent=seminario&rss=0&id=6276