Seminari - Dipartimento Computer Science Seminari - Dipartimento Computer Science validi dal 18.01.2020 al 18.01.2021. Course on SageMath 20-23 Jan. 2020 Relatore: Prof. Péter Burcsi; Provenienza: Eötvös Loránd Univ. Budapest, Hungary; Data inizio: 2020-01-20; Note orario: 20-23 Jan. 2020; Riassunto: This is to inform students of the 8-hour course on the softwareSageMath, given by Prof. Peacute;ter Burcsi from Eouml;tvouml;s Loraacute;nd University, Budapest, Hungary, from 20 to 23 Jan. 2020. All students of all levels are welcome (PhD, master=magistrali, bachelor=triennalisti;computer science, mathematics, bioinformatics), as well as anyone else who is interested. Students are required to register for the course by sending an email to Laura Marcazzan, Short description: We give an overview and a brief introduction to the SAGE computer algebra system. SageMath (previously Sage or SAGE, System for Algebra and Geometry Experimentation) is a mathematical software with features covering many aspects of math, including algebra, combinatorics, numerical mathematics, number theory, calculus. Course times: Mon. Jan 20, 2020ndash;16.10-17.50 ndash; LAB GAMMA Tue. Jan 21, 2020 ndash; 17.00-18.40 ndash; LAB GAMMA Wed. Jan 22, 2020 ndash; 16.10-17.50 ndash; LAB GAMMA Thu. Jan 23, 2020 ndash; 12.50-14.30 ndash; LAB DELTA For more information, see the attached flyer. The course is an optional part of the PhD program. Bachelor or master s tudents (computerscience, mathematics, or bioinformatics) can acquire 1 CFU. Mon, 20 Jan 2020 00:00:00 +0100 Machine Learning Training: Research Challenges and Opportunities for the Distributed System Community Relatore: Giovanni Neglia; Provenienza: INRIA, Sophia Antipolis, Francia; Data inizio: 2020-01-28; Ora inizio: 11.00; Note orario: Sala Verde; Riassunto: In this talk, I will support the thesis that the Dystributed System community is not meant to simply apply machine learning (ML) tools to solve specific problems, but can also contribute to design faster and more efficient distributed ML systems both for training and inference. I will first introduce machine learning training and show that computational speedups directly translate into better ML models. I will then explain why design choices for ML systems are inevitably entangled with optimization and statistical considerations. Finally, I will provide two examples from my recent research activity: dynamic (TCP-like) adaptation of the number of ML workers, and topology design. Tue, 28 Jan 2020 11:00:00 +0100 Combinatorial Strategies for Modern Biology [2 ECTS, MAT/03] Relatore: Margherita Maria Ferrari; Provenienza: University of South Florida; Data inizio: 2020-04-15; Note orario: Starting date; Referente interno: Giuseppe Mazzuoccolo; Riassunto: The purpose of these lectures is twofold. On one hand, we want to highlight how classical notions in combinatorics are applied to advance our understanding of biological/chemical processes. On the other hand, we want to show that such processes lead to new mathematical objects and drive new areas of research. We will give the biological background for DNA self-assembly and DNA recombination processes, as well as RNA structure formation. We will provide the combinatorial tools, mainly graph-theoretic approaches, to model and analyze such problems, and discuss some open questions related to these models. Wed, 15 Apr 2020 00:00:00 +0200 Euler-Poincaré variational principles and applications to fluid dynamics - [1 ECTS, MAT/07] Relatore: Prof. Cesare Troncy; Provenienza: University of Surrey - UK -; Data inizio: 2020-04-20; Referente interno: Nicola Sansonetto; Riassunto: Starting from Poincareacute;#39;soriginal work from 1901, this lecture series offers a brief overview of the reduction by symmetry for Hamilton#39;s variational principle on Lie groups. After considering the simple case of a free rigid body, different types of examples will be covered before focusing on fluid dynamics. Eventually, the last lectures present a brief introduction to the application of these methods to the dynamics of nematic liquid crystals, in both ideal and dissipative cases. Mon, 20 Apr 2020 00:00:00 +0200