Introduction

About the school

Italian Computer Science PhD granting institutions under the auspices of GRIN, organizes an annual school offering three graduate-level courses aimed at first-year PhD students in Computer Science. In addition to introducing students to timely research topics, the school is meant to promote acquaintance and collaboration among young European researchers. The 2019 edition of the School is the 25th in the series.
The school will offer 3 courses each consisting of 13 hours of lectures:

  • Multitask learning and learning-to-learn: a statistical learning perspective
    Prof. Massimiliano Pontil - Istituto Italiano di Tecnologia & University College London
  • Software security across abstraction layers (SS)
    Frank Piessens - KU Leuven
  • Internet of things: a data oriented approach
    Luciano Bononi- University of Bologna

A final evaluation for each course is possible through a final exam or project as determined by the instructor. The daily schedule admits laboratory and/or working group activities to be organized in addition to the lectures.
The registration fee for the School is 550.00 Euro and includes all local expenses from the evening of 10 March to 15 March afternoon including all meals and on-site lodging in double-occupancy rooms. A reduced registration fee of 300.00 Euro is available for local students which will not use the on-site lodging facilities (it includes local expenses for the lectures, coffee breaks and lunches). It is possible to require one additional night for the students that want to leave on Saturday the 16th. In this case the additional cost is 50 Euros.
Attendance is limited to 50 students and will be allocated on a first-come-first-served basis.

Courses

Multitask learning and learning-to-learn: a statistical learning perspective

Prof. Massimiliano Pontil , Istituto Italiano di Technologia & University College London

Abstract: A fundamental limitation of standard machine learning methods is the cost incurred by the preparation of the large training samples required for good generalization. A potential remedy is offered by multi-task learning: in many cases, while individual sample sizes are rather small, there are samples to represent a large number of learning tasks, which share some constraining or generative property. If this property is sufficiently simple it should allow for better learning of the individual tasks despite their small individual sample sizes. The course review a wide class of multi-task learning methods, describe techniques to solve the underlying optimization problems and present an analysis of the generalization performance of these learning methods which provides a proof of the superiority of multi-task learning under specific conditions. We also highlight the link between MTL and learning-to-learn (or meta-learning) and reviews recent efforts in this direction.

Software security across abstraction layers (SS)

Prof. Frank Piessens, KU Leuven

Abstract: The execution infrastructure for today's software applications is typically structured in a layered architecture where each layer offers abstractions that are supposed to hide some of the implementation details of lower layers.
Many security problems that occur in software applications however are very much cross-layer: attacks against applications that are running on top of the execution infrastructure often rely at least to some extent on implementation details of one or more lower layers.
The objective of this course is to study the problem of software security across these various abstraction layers. The course starts with an overview of the field of software security, and the definition of the core concepts of the field. Next, it covers the security of software systems against attackers that have access to lower abstraction layers.
The course will cover both attack techniques as well as defense techniques. On the attack side, we give an overview of influential attack techniques ranging from classic buffer overflows to the most recent micro-architectural attacks like Spectre, Meltdown and Foreshadow. On the defense side, the emphasis will be on techniques for which strong formal security guarantees can be given, as well as on the limitations of such formal guarantees in the field of security.

Internet of things: a data oriented approach

Prof. Luciano Bononi, Universty of Bologna

Abstract: We will introduce the enabling technologies, protocols, software architectures and applications for the development of the Internet of Things (IoT) paradigm. After a short introduction to pervasive computing and the emerging fields of applications (e.g. Industry 4.0, domotics, intelligent transportation systems, wearable devices, etc.) the course will provide an illustration of the enabling components, technologies and standards of IoT systems. These will include the wireless communications among end-devices and towards infrastructures, data processing, languages for the development of applications and prototypes (e.g. Arduino, STM32 Nucleo, etc.). Specifically, the components of a typical IoT system will be illustrated by following a data-oriented approach: from sensor to gateway (data generation on behalf of sensors to data transmission in WSAN, WPAN, WLAN), from gateway to cloud (up to cloud streaming and storages), and from cloud to applications (including the data processing and integration in complex software systems). A short illustration on open issues and bottlenecks will conclude the seminar.

Programmes


Multitask learning and learning-to-learn: a statistical learning perspective (ML)
Software security across abstraction layers (SS)
Internet of things: a data oriented approach (IoT)

2019
10/03
11/03
12/03
13/03
14/03
15/03
Sun
Mon
Tue
Wed
Thu
Fri
08.00-09.00
breakfast
09.00-10.00 SS SS ML ML IoT
10.00-11.00 SS SS ML ML IoT
11.00-11.30 coffee break
11.30-12.30 IoT IoT SS ML IoT
12.30-13.30 IoT IoT SS ML IoT
13.30-15.00 lunch
15.00-16.00 SS ML ML SS departure
16.00-17.00 SS ML ML SS -
17.00-17.30coffee break
17.00-17.30arrival IoT ML SS IoT -
17.30-18.30 IoT ML SS IoT-

ORGANIZATION

Scientific Organizing Committee


Nicolò Cesa Bianchi, University of Milano
Pierpaolo Degano, University of Pisa
Maurizio Gabbrielli, University of Bologna

Local Organization


Andrea Bandini, CeUB
Monica Michelacci, CeUB
Michela Schiavi, CeUB
Tong Liu, University of Bologna, Italy

Registration

The registration fee for the School is 550.00 Euro and includes all local expenses from the evening of 10 March to 15 March afternoon including all meals and on-site lodging in double-occupancy rooms. A reduced registration fee of 300.00 Euro is available for local students which will not use the on-site lodging facilities (it includes local expenses for the lectures, coffee breaks and lunches). It is possible to require one additional night for the students that want to leave on Saturday the 16th. In this case the additional cost is 50 Euro. Attendance is limited to 50 students and will be allocated on a first-come-first-served basis.

In order to register, all applicants must fill the form available at the following link: REGISTRATION FORM.

Venue

BISS events are held in the University Residential Center located in the small medieval hilltop town of Bertinoro. This town is in Emilia Romagna about 50km east of Bologna at an elevation of 230m above sea level. View More

Via Frangipane, 6 in Bertinoro, Italy

+39 0543 446500

segreteria@ceub.it

http://www.ceub.it

Past Editions

BISS 2019:

  • Internet of things: a data oriented approach
  • Multitask learning and learning-to-learn: a statistical learning perspective
  • Software security across abstraction layers

BISS 2018:

  • Provable security for low level execution platforms
  • Distributed models, MapReduce and large scale algorithms
  • Elements of Quantum Computation

BISS 2017:

  • Approximation Algorithms
  • Probabilistic Graphical Models in Intelligent Systems
  • Kleene algebra with tests and applications to network programming

BISS 2016:

  • ADVANCED TOPICS IN PROGRAMMING LANGUAGES
  • MODELS AND LANGUAGES FOR SERVICE-ORIENTED AND CLOUD COMPUTING
  • ALGORITHMIC METHODS FOR MINING LARGE GRAPHS

BISS 2015:

  • Game Theory: Models, Numerical Methods, and Applications
  • Protection of sensitive information
  • Introduction to Modern Cryptography

BISS 2014:

  • Big Data Analysis of Patterns in Media Content
  • An Introduction to Probabilistic and Quantum Programming
  • Development of dynamically evolving and self-adaptive software

BISS 2013:

  • Foundations of Security: Cryptography, Protocols, Trust
  • Stochastic Process Algebras for Quantitative Analysis
  • Shape and Visual Apperance Acquisition for Photo-realistic Visualization

BISS 2012:

  • Algorithms for the web and for social networks
  • Software Verification and Interactive Theorem Proving
  • Regularization methods for high dimensional learning

BISS 2011:

  • Computational Aspects of Game Theory
  • Trust in Anonymity Networks (TAN)
  • Information Integration (II)
  • Model Checking: From Finite-state to Infinite-state Systems (MCFIS)