NSCPHD1233 Online Learning Summer School
- Subject area: Online Learning
Online learning is a broad subfield of machine learning covering problems involving iterative predictions/actions by the learner and revelation of the outcomes. It includes problems like stock market prediction, ads placement on the Internet, medical treatments, robotics, and many more. It involves dealing with continuous streams of data, handling non-stationary environments, coping with adversarial opponents, and many other challenging practical problems. Online learning has changed the way data is processed and unveiled a new world of approaches to personalization, large-scale data processing, and many other challenges of our data-intensive era.
- Scientific content
The course will consist of 5 days of lectures and exercises and cover the following topics in online learning:
Day 1: Online learning with full information feedback and relations to optimization, to be taught by Shai Shalev-Shwartz.
Day 2 & 3: Online learning with limited (bandit) feedback in stochastic and adversarial environments, to be taught by Nicolò Cesa-Bianchi and Peter Auer.
Day 4: Reinforcement learning, to be taught by Csaba Szepesvári and Peter Auer.
Day 5: "The space of online learning problems" - interpolations between various online learning settings, to be taught by Yevgeny Seldin.
- Learning outcome
After participating in the course the students should gain the following competencies:
- Knowledge of basic concepts in online and reinforcement learning
- Ability to formulate real-life problems in the language of online or reinforcement learning
- Knowledge of algorithms and evaluation measures for online learning problems
- Knowledge of lower bounds on the performance of online learning algorithms
- Ability to apply online learning algorithms to problems in their research
Knowledge about the tools for analysis and development of online learning algorithms
- Category
- Hours
- Lectures
- 40
- Preparation
- 10
- Project work
- 15
- Total
- 65
- Credit
- 2,5 ECTS
- Type of assessment
- Continuous assessment under invigilation
Course information
- Language
- English
- Course code
- NSCPHD1233
- Credit
- 2,5 ECTS
- Level
- Ph.D.
- Duration
- 5 days
- Placement
- Summer
- Schedule
- The course is a 5-day course taking place from Sunday, 28 June 2015 until Thursday, 2 July 2015.
- Course capacity
- Unlimited
- Study board
- Natural Sciences PhD Committee
Contracting department
- Department of Computer Science
Course responsibles
- Yevgeny Seldin (6-7b6d746c7176486c7136737d366c73)
- Christian Igel (4-6f6d6b72466a6f34717b346a71)
Lecturers
Peter Auer
Nicolò Cesa-Bianchi
Yevgeny Seldin
Shai Shalev-Shwartz
Csaba Szepesvári