Przemyslaw Uznanski: Catalogue data in Spring Semester 2018 |
| Name | Dr. Przemyslaw Uznanski |
| Department | Computer Science |
| Relationship | Lecturer |
| Number | Title | ECTS | Hours | Lecturers | |
|---|---|---|---|---|---|
| 252-3002-00L | Algorithms for Database Systems  Limited number of participants. | 2 credits | 2S | P. Widmayer, P. Uznanski | |
| Abstract | Query processing, optimization, stream-based systems, distributed and parallel databases, non-standard databases. | ||||
| Learning objective | Develop an understanding of selected problems of current interest in the area of algorithms for database systems. | ||||
| 252-4230-00L | Advanced Algorithms and Data Structures Um das vorhandene Angebot optimal auszunutzen, behält sich das D-INFK vor, Belegungen von Studierenden zu löschen, die sich in mehreren Veranstaltungen dieser Kategorie eingeschrieben haben, bereits die erforderlichen Leistungen in dieser Kategorie erbracht haben oder aus anderen organisatorischen Gründen nicht auf die Belegung der Veranstaltung angewiesen sind. | 2 credits | 2S | P. Widmayer, S. Leucci, P. Uznanski | |
| Abstract | We will look into modern approaches of algorithms and data structures. A few breakthrough and highly influential papers from the general area of algorithms, from the past 20 years will be selected for students to study. | ||||
| Learning objective | Develop an understanding of modern techniques and paradigms in the design of algorithms and data structures. | ||||
| Content | Topics include (but are not exhausted by): -graph algorithms, -text algorithms, -approximation algorithms, -algebra in algorithms, -streaming algorithms, -conditional lower bounds, -sparsification, -randomness in algorithms, -sampling. | ||||
| Prerequisites / Notice | Algorithms and Data Structures, or equivalent. | ||||
| 263-4312-00L | Advanced Data Structures | 5 credits | 2V + 2U | P. Uznanski | |
| Abstract | Data structures play a central role in modern computer science and are essential building blocks in obtaining efficient algorithms. The course covers major results and research directions in data structures, that (mostly) have not yet made it into standard computer science curriculum. | ||||
| Learning objective | Learning modern models of computation. Applying new algorithmic techniques to the construction of efficient data structures. Understanding techniques used in both lower- and upper- bound proofs on said data structures. | ||||
| Content | This course will survey important developments in data structures that have not (yet) worked their way into the standard computer science curriculum. Though we will cover state of the art techniques, the presentation is relatively self-contained, and only assumes a basic undergraduate data structures course (e.g., knowledge of binary search trees). The course material includes (but is not exhausted by): - computation models and memory models - string indexing (suffix trees, suffix arrays) - search trees - static tree processing (Lowest Common Ancestor queries, Level Ancestry queries) - range queries on arrays (queries for minimal element in a given range) - integers-only data structures: how to sort integers in linear time, faster predecessor structures (van Emde Boas trees) - hashing - dynamic graphs connectivity | ||||
| Prerequisites / Notice | This is a highly theoretical course. You should be comfortable with: - algorithms and data structures - probability Completing Algorithms, Probability, and Computing course (252-0209-00L) is a good indicator. | ||||