TY  - RPRT
T1  - b-Bit Minwise Hashing in Practice
Y1  - 2013
A1  - Li, Ping
A1  - Shrivastava, Anshumali
A1  - König, Arnd Christian
AB  - b-Bit Minwise Hashing in Practice Li, Ping; Shrivastava, Anshumali; König, Arnd Christian Minwise hashing is a standard technique in the context of search for approximating set similarities. The recent work [26, 32] demon- strated a potential use of b-bit minwise hashing [23, 24] for ef- ficient search and learning on massive, high-dimensional, binary data (which are typical for many applications in Web search and text mining). In this paper, we focus on a number of critical is- sues which must be addressed before one can apply b-bit minwise hashing to the volumes of data often used industrial applications.
PB  - Cornell University
UR  - http://hdl.handle.net/1813/37986
ER  - 

TY  - RPRT
T1  - Fast Near Neighbor Search in High-Dimensional Binary Data
Y1  - 2013
A1  - Shrivastava, Anshumali
A1  - Li, Ping
AB  - Fast Near Neighbor Search in High-Dimensional Binary Data Shrivastava, Anshumali; Li, Ping Numerous applications in search, databases, machine learning, and computer vision, can benefit from efficient algorithms for near neighbor search. This paper proposes a simple framework for fast near neighbor search in high-dimensional binary data, which are common in practice (e.g., text). We develop a very simple and effective strategy for sub-linear time near neighbor search, by creating hash tables directly using the bits generated by b-bit minwise hashing. The advantages of our method are demonstrated through thorough comparisons with two strong baselines: spectral hashing and sign (1-bit) random projections.
PB  - Cornell University
UR  - http://hdl.handle.net/1813/37987
ER  - 

TY  - RPRT
T1  - Presentation: Predicting Multiple Responses with Boosting and Trees
Y1  - 2013
A1  - Li, Ping
A1  - Abowd, John
AB  - Presentation: Predicting Multiple Responses with Boosting and Trees Li, Ping; Abowd, John Presentation by Ping Li and John Abowd at FCSM on November 4, 2013
PB  - Cornell University
UR  - http://hdl.handle.net/1813/40255
ER  -