Department of Computer Science | Institute of Theoretical Computer Science
|Organization:||Michael Böhlen, Peter Widmayer and Przemyslaw Uznanski|
|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.
|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|
|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|