Computational Aspects of Machine Learning

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Computational Aspects of Machine Learning Seminar in Winter 2014 Preliminary meeting Valeriy Khakhutskyy, Kilian Röhner, Emily Mo-Hellenbrand June 26, 2014 Seminar in Winter 2014Preliminary meeting, June 26, 2014 1

About the Seminar What is Machine Learning? Intersection of applied mathematics, informatics, and computational science. Concerns methods and systems, that learn from data. Generate knowledge from experience. Seminar in Winter 2014Preliminary meeting, June 26, 2014 2

About the Seminar What is Machine Learning? Intersection of applied mathematics, informatics, and computational science. Concerns methods and systems, that learn from data. Generate knowledge from experience. What are we up to in the seminar? Amount of data grows rapidly. Models become more complex. HPC systems get more sophisticated with every generation. The demands of customers are rising. We study recent concepts and algorithms that cope with these challenges. Seminar in Winter 2014Preliminary meeting, June 26, 2014 2

Topics 1. Parallelisation paradigms and parallel performance models 2. Large scale Bayesian inference 3. Approximate k-nearest neighbors search 4. Random projection matrices, feature hashing 5. Speeding-up deep learning 6. Advanced MCMC algorithms 7. Online learning 8. Real-time data mining with guaranteed throughput 9. Data Mining with sparse grids 10. Fault detection in data streams 11. Map-reduce for machine learning algorithms 12. Your own idea? Seminar in Winter 2014Preliminary meeting, June 26, 2014 3

Seminar classification & Prerequisites Seminar classification Hauptseminar: For advanced bachelor students or master students. Fields of Study: Informatics, Information Systems, Games Engineering, Master CSE. 2 SWS, 4 ECTS. Seminar in Winter 2014Preliminary meeting, June 26, 2014 4

Seminar classification & Prerequisites Seminar classification Hauptseminar: For advanced bachelor students or master students. Fields of Study: Informatics, Information Systems, Games Engineering, Master CSE. 2 SWS, 4 ECTS. Prerequisites mathematics: linear algebra, probability theory, calculus, and convex optimisation. machine learning: basic concepts. Soft skills: presentation techniques, scientific paper stuying and writing. Seminar in Winter 2014Preliminary meeting, June 26, 2014 4

Organisatorial Information Course of the seminar Weekly sessions of 90 Minutes: 45 Minutes presentation followed by a discussion. Extended abstract: 1 page article style with motivation, key concepts and results. Paper: min. 5 pages in IEEE format (excl. sources). Language: English 10 participants Blind peer-review process: 2 reviews per student. Session chairs. Attendance and active participation at all seminar sessions is mandatory. Seminar in Winter 2014Preliminary meeting, June 26, 2014 5

Organisatorial Information Course of the seminar Weekly sessions of 90 Minutes: 45 Minutes presentation followed by a discussion. Extended abstract: 1 page article style with motivation, key concepts and results. Paper: min. 5 pages in IEEE format (excl. sources). Language: English 10 participants Blind peer-review process: 2 reviews per student. Session chairs. Attendance and active participation at all seminar sessions is mandatory. Dates, Time and Location Wednesdays, 10 a.m.. First session: October 22th. Last session: December 17th (two talks). Room: MI 02.07.023. Seminar in Winter 2014Preliminary meeting, June 26, 2014 5

Organisatorial Information Deadlines 1 week before the talk: submission of an extended abstract The days of the talk: submission of a preliminary paper for review 1 week after the talk: receiving comments from reviewers 2 week after the talk: submission of the final paper Seminar in Winter 2014Preliminary meeting, June 26, 2014 6

Application Seminar matching system: Available from July 4th until July 8th. Our application system: Available from now until July 8th (link on course website). 3 topic preferences. Motivation letter. After that... Until end of july: matching of seminar participants to topics. Use the semester break to prepare your abstract, paper and presentation. Seminar in Winter 2014Preliminary meeting, June 26, 2014 7

http://www5.in.tum.de/wiki/index.php/hauptseminar_ Computational_Aspects_of_Machine_Learning_-_Winter_14 Seminar in Winter 2014Preliminary meeting, June 26, 2014 8