DerStandard

Thu 14:00 – 16:00 08.03.2012 Seminarraum Gödel
Thu 14:00 – 16:00 15.03.2012 Seminarraum Gödel
Thu 14:00 – 16:00 22.03.2012 Seminarraum Gödel
Thu 14:00 – 16:00 19.04.2012 Seminarraum Gödel
Thu 14:00 – 16:00 26.04.2012 Seminarraum Gödel
Thu 14:00 – 16:00 03.05.2012 Seminarraum von Neumann
Thu 14:00 – 16:00 24.05.2012 Seminarraum Gödel
Thu 14:00 – 16:00 31.05.2012 Seminarraum Gödel
Thu 14:00 – 16:00 14.06.2012 Seminarraum Gödel
Thu 14:00 – 16:00 21.06.2012 Seminarraum Gödel
Thu 14:00 – 16:00 28.06.2012 Seminarraum Gödel

Registration and further details in TISS.

Goals:

The goal is to get acquainted with the theory of coalgebra and its use in computer science. Also, along the way, the students will get to know some category theory notions that are needed for basic constructions and results in coalgebra. The course is meant for computer science students (possibly also some mathematics students) interested in computer science theory. If you are a student interested in formal methods, concurrency theory, and/or automata, and/or you always wondered what is category theory good for, then this may be the right course for you.

Content:

The theory of coalgebra is a relatively recent (20 years old) unifying theory at the abstract end of formal methods. It is a (one could say “the”) theory of dynamic systems, of states and observations. Coalgebras allow for a uniform treatment of many different types of automata (e.g. deterministic, nondeterministic, probabilistic, and weighted), their behavior, and their corresponding modal logics. These topics will be covered within the course.

How students are evaluated:
The evaluation will depend on presented papers and the examination at the end of term.

ECTS-Breakdown (3 ECTS):

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30 hours: lectures
23 hours: exercises
23 hours: preparation for examination
2 hours: examination
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75 hours: total
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VO Inductive Rule Learning

Mon 08:30 – 13:00 12.03.2012 seminar room Gödel
Tue 08:30 – 13:00 13.03.2012 seminar room Gödel
Mon 12:30 – 17:00 19.03.2012 seminar room Gödel
Mon 08:30 – 13:00 26.03.2012 seminar roomGödel
Tue 08:30 – 13:00 27.03.2012 seminar room Gödel

Registration and further details in TISS.

Aim of the course:

The goal of this course to familiarize the student with fundamental concepts of machine learning in general and inductive rule learning in particular. It will focus both on a predictive setting, where the goal is to learn a set of rules that collectively make a prediction, and a descriptive setting, where the goal is to learn a set of rules that collectively explain the data. The learning techniques will be first illustrated for concept learning tasks in propositional logic, but later also extended to first-order logic as well as to structured prediction tasks.

There are no prerequisites except for basic knowledge about algorithms. The course is thus not only suited for computer science students but for all students that have a strong interest in machine learning in data analysis.

Content:

Rules – the clearest, most explored and best understood form of knowledge representation – are particularly important for data mining, because they offer the best tradeoff between human and machine understandability. This course will present algorithms for automated rule learning and discovery as investigated in classical machine learning and modern data mining. We will start with algorithms for learning single rules in propositional logic, move on to learning rule sets with the covering or separate-and-conquer algorithm, inductive logic programming algorithms for learning rules in first-order logic, and discuss approaches that allow to make predictions in structured output spaces. Elementary data mining algorithms such as association rule discovery will also be covered, as well as essential concepts of machine learning and data mining. It is thus suitable as a first introduction into these research areas.

Most of the course will follow the book “Foundations of Rule Learning” that will appear in Springer-Verlag in early 2012.

http://www.amazon.de/Rule-Learning-Essentials-Relational-Technologies/dp/3540751963

Edmund M. Clarke is among the leading computer scientists of our times. As a professor at Harvard, and, since 1982, at Carnegie Mellon University, he and his group have not only laid the theoretical and logical foundations of model checking (ACM Turing Award, 2007), but also pioneered model checking as a powerful tool for industrial hardware and software engineering.

On January 26, 2012, as part of the festive opening of the Vienna Center for Logic and Algorithms, Prof. Clarke will be awarded an honorary doctorate from TU Vienna in recognition of his contributions to Computer Science.

Below: Ed Clarke at the Opening Press Conference of the RiSE Network in March 2011

We will celebrate the opening of VCLA with a Symposium on January 25. See the VCLA website for details.

Details are available from the VCLA website.

Further information is available from the workshop’s website.

Photos by Damien Zufferey (full gallery):