Organization:	Michael Böhlen, Peter Widmayer and Przemyslaw Uznanski
Teaching language:	English
Level:	PhD, MSc and advanced BSc students
Academic Year:	Spring 2018
Dates:	Friday 23.2.2018 14.15-15.00h ETHZ CAB H 52 Saturday 28.4.2018 9.30-15.00h ETHZ CAB H 52 Saturday 19.5.2018 TBD

Overview and objectives: The area of this year's seminar is Locality Hashing, Similarity, Nearest Neighbours. Students learn how to critically read and study research papers, how to summarize the contents of a paper, and how to present it in a seminar.

Teaching format: Each participant writes a self-contained report of about 10 pages and gives a 30 minutes presentation (blackboard, without a computer). Each participant has a buddy. Buddies read the report, make suggestions for improvements, and help with the presentation (e.g., dry runs). The first version of the report is due three weeks before the date of the presentation, and will be discussed with the buddy and the professor about one week before the presentation. The final versions of the report are due one week before the date of the seminar.

Setup and Organization: The setup of the seminar will be discussed Friday February 23, 2018 from 14:15 until 15:00 in room CAB H 52 at ETHZ. At the first meeting the available slots for the seminar will be distributed and papers will be assigned.

Presentations:

• Saturday April 28, 9.30-15.00h ETHZ CAB H 52.
• Saturday May 19, TBD, 9am.

Participation at all three meetings is compulsory for students. The assessment depends on the quality of the report, presentation, active participation during the seminar, and input as a buddy.

Useful links:

• organizational slides
• How to give talks and read papers: link
• example of a good report

Saturday 28.4.2018:

Paper	Student	Advisor	Buddy	Report
Gionis, Indyk, Motwani: Similarity Search in High Dimensions via Hashing VLDB'99	Timothy Pescatore	Michael Böhlen	Olga Klimashevska	report
Indyk: Dimensionality Reduction Techniques for Proximity Problems SODA'00	Dhivyabharathi Ramasamy	Przemysław Uznański	Stefan Tiegel	report
Indyk: Stable Distributions, Pseudorandom Generators, Embeddings, and Data Stream Computation FOCS'00	Luise Arn	Przemysław Uznański	Nicolas Gordillo	report
Indyk, Motwani: Approximate Nearest Neighbors: Towards Removing the Curse of Dimensionality STOC'98	Lukas Arnold	Peter Widmayer	Wanja Chresta	report
Datar, Immorlica, Indyk, Mirrkoni: Locality-Sensitive Hashing Scheme Based on p-Stable Distributions SoCG'04	Alphonse Mariyagnanaseelan	Peter Widmayer	Sebastian Sanchez	report
Broder, Glassman, Manasse, Zweig: Syntactic clustering of the Web Computer Networks and ISDN Systems	Amos Madalin Neculau	Peter Widmayer	Michael Studer	report

Saturday 19.5.2018:

Paper	Student	Advisor	Buddy
Cormode, Datar, Indyk, Muthukrishnan: Comparing Data Streams Using Hamming Norms (How to Zero In) VLDB'02	Stefan Tiegel	Michael Böhlen	Lukas Arnold
Andoni, Krauthgamer, Razenshteyn: Sketching and Embedding are Equivalent for Norms STOC'15	Wanja Chresta	Peter Widmayer	Dhivyabharathi Ramasamy
Cormode, Muthukrishnan: An Improved Data Stream Summary: The Count-Min Sketch and its Applications J. Algorithms	Liu Bingyan	Przemysław Uznański	Alphonse Mariyagnanaseelan
Andoni, Indyk, Laarhoven, Razenshteyn, Schmidt: Practical and Optimal LSH for Angular Distance NIPS'15	Nicolas Gordillo	Przemysław Uznański	Timothy Pescatore
Andoni, Indyk: Near-Optimal Hashing Algorithms for Approximate Nearest Neighbor in High Dimensions FOCS'06	Michael Studer	Peter Widmayer	Liu Bingyan
Tang, U, Cai, Mamoulis, Cheng: Earth Mover’s Distance based Similarity Search at Scale VLDB'13	Olga Klimashevska	Michael Böhlen	Amos Madalin Neculau
Matusevych, Smola, Ahmed: Hokusai — Sketching Streams in Real Time UAI'12	Sebastian Sanchez	Michael Böhlen	Luise Arn