Training and Research

Credits

3

Language

English

Class attendance

Free Choice

Location

VERONA

Learning objectives

Machine Teaching studies how efficiently a teacher can guide a learner to acquire a target hypothesis.
The classic works date back to the 1990’s [Shinohara91,Goldman95] consider the setting where the teacher sends in one shot a set of labeled examples to the learner, who then has to output the correct target hypothesis. In the more recent studies, the focus has been on the interactive setting, where the Teacher and Leaner interact over multiple rounds. In each round, the teacher sends examples to the learner, who returns some feedback; this process continues until the learner reaches the target hypothesis (or a good approximation of it). Machine teaching models have proved useful in several contexts, e.g., crowd sourcing, intelligent tutoring systems, analysis of training set attacks. Moreover, commercial tools are under development by the Microsoft Machine Teaching Group, as detailed on their web page, which are based on, or employ, the paradigm of machine teaching, e.g., PICL, which leverages the selection of examples that maximize the training value of the interaction with the teacher; LUIS for natural language understanding; and other projects on building models for autonomous systems, and tools enabling non-experts of machine learning to build their models.

Prerequisites and basic notions

Basic knowledge of algorithm analysis and discrete probability

Program

Foundations: From PAC learning to Active learning, to Machine Teaching; Teaching dimension concepts (batch, sequential, recursive, VC-dimension and sample compression); Interactive Machine Teaching and Black Box machine teaching; Application: human/robot/computer interaction, training-set attacks, crowdsourcing.

Bibliography

Visualizza la bibliografia con Leganto, strumento che il Sistema Bibliotecario mette a disposizione per recuperare i testi in programma d'esame in modo semplice e innovativo.

Didactic methods

Lectures (blackboard and slides)

Learning assessment procedures

Reading assignments and oral discussion

Students with disabilities or specific learning disorders (SLD), who intend to request the adaptation of the exam, must follow the instructions given HERE

Assessment

Understanding of the basic concepts and ability to apply them in new contexts

Criteria for the composition of the final grade

The result will be Pass/Fail

Scheduled Lessons

When Classroom Teacher topics
Tuesday 25 February 2025
12:30 - 16:30
Duration: 4:00 AM
Ca' Vignal 2 - G [96 - terra] Ferdinando Cicalese Machine Teaching - 1
Wednesday 26 February 2025
12:30 - 16:30
Duration: 4:00 AM
Ca' Vignal 2 - G [96 - terra] Ferdinando Cicalese Machine Teaching - 2
Friday 28 February 2025
12:30 - 16:30
Duration: 4:00 AM
Ca' Vignal 2 - M [68 - 1°] Ferdinando Cicalese Machine Teaching - 3

Sustainable Development Goals - SDGs

This initiative contributes to the achievement of the Sustainable Development Goals of the UN Agenda 2030. More information on sustainability

PhD school courses/classes - 2024/2025

Please note: Additional information will be added during the year. Currently missing information is labelled as “TBD” (i.e. To Be Determined).

1. PhD students must obtain a specified number of CFUs each year by attending teaching activities offered by the PhD School.
First and second year students must obtain 8 CFUs. Teaching activities ex DM 226/2021 provide 5 CFUs; free choice activities provide 3 CFUs.
Third year students must obtain 4 CFUs. Teaching activities ex DM 226/2021 provide 2 CFUs; free choice activities provide 2 CFUs.
More information regarding CFUs is found in the Handbook for PhD Students: https://www.univr.it/phd-vademecum

2. Registering for the courses is not required unless explicitly indicated; please consult the course information to verify whether registration is required or not. When registration is actually required, instructions will be sent well in advance. No confirmation e-mail will be sent after signing up. Please do not enquiry: if you entered the requested information, then registration was silently successful.

3. When Zoom links are not explicitly indicated, courses are delivered in presence only.

4. All information we have is published here. Please do not enquiry for missing information or Zoom links: if the information you need is not there, then it means that we don't have it yet. As soon as we get new information, we will promptly publish it on this page.

Summary of training activities

Teaching Activities ex DM 226/2021: Linguistic Activities

Teaching Activities ex DM 226/2021: Research management and Enhancement

Teaching Activities ex DM 226/2021: Statistics and Computer Sciences

Teaching Activities: Free choice

THE EMPIRICAL PHENOMENOLOGICAL METHOD (EPM): THEORETICAL FOUNDATION AND EMPIRICAL APPLICATION IN EDUCATIONAL AND HEALTHCARE FIELDS

Credits: 2

Language: English

Teacher:  Luigina Mortari

DOTTORATO E MERCATO DEL LAVORO: WORKSHOP FORMATIVI PER DOTTORANDI E NEO-DOTTORI DI RICERCA

Credits: 4

Language: Italian

ARE YOU SURE YOU CAN DEFEAT A CHATBOT?

Credits: 1

Language: Italian

MEETING UKRAINE: THE IMPACT OF WAR AND FUTURE OPPORTUNITIES

Credits: 1

Language: Italian

OPEN SCIENCE: THE MIGHTY STICK AGAINST "BAD" SCIENCE

Credits: 2

Language: English

Teacher:  Michele Scandola

Differential diagnosis of demyelinating diseases of the central nervous system

Credits: 2

Language: Italiano; English

Teacher:  Alberto Gajofatto

EMOTIONS, BELIEFS, AND SKILLS TO FACE CLIMATE CHANGE AND EMBRACE CLIMATE ACTION

Credits: 0,5

Language: English

COMPUTATIONAL MECHANISMS UNDERLYING SENSORIMOTOR LEARNING

Credits: 4,5

Language: English

Teacher:  Matteo Bertucco

CSF DYNAMICS: ANATOMICAL AND FUNCTIONAL FEATURES

Credits: 0,5

Language: English

Teacher:  Alberto Feletti

sleep related disoders: focus on REM and NREM parasomnia and SR movement disorders

Credits: 1,5

Language: italiano o inglese

Teacher:  Elena Antelmi

Tecniche di immagine per l'analisi della composizione corporea

Credits: 1

Language: Inglese/English

Teacher:  Carlo Zancanaro

Tecniche di ricerca in neuroscienze: misurare e modulare l'attività neuronale

Credits: 2,3

Language: non prevista

Teacher:  Giuseppe Busetto

Course lessons
PhD Schools lessons

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Guidelines for PhD students

Below you will find the files that contain the Guidelines for PhD students and rules for the acquisition of ECTS credits (in Italian: "CFU") for the Academic Year 2023/2024.

Documents

Title Info File
File pdf Dottorandi: linee guida generali (2024/2025) pdf, it, 104 KB, 29/10/24
File pdf PhD students: general guidelines (2024/2025) pdf, en, 107 KB, 29/10/24