We propose a considerably faster approximation of the well known SIFT method. The main idea is to use efficient data structures for both, the detector and the descriptor. The detec...
Top-k approximate querying on string collections is an important data analysis tool for many applications, and it has been exhaustively studied. However, the scale of the problem ...
Approximate Nearest Neighbor (ANN) methods such as Locality Sensitive Hashing, Semantic Hashing, and Spectral Hashing, provide computationally ecient procedures for nding objects...
The approximate string matching problem is to find all locations at which a query of length m matches a substring of a text of length n with k-or-fewer differences. Simple and prac...
We study graph partitioning problems on graphs with edge capacities and vertex weights. The problems of b-balanced cuts and k-balanced partitions are unified into a new problem ca...
Guy Even, Joseph Naor, Satish Rao, Baruch Schieber