We understand selection by intersection as distinguishing a single element of a set by the uniqueness of its occurrence in some other set. More precisely, given two sets A and B, i...
We present efficient algorithms for computing very sparse low distortion spanners in distributed networks and prove some non-trivial lower bounds on the tradeoff between time, spar...
Abstract--In the design of distributed quantization systems one inevitably confronts two types of constraints--those imposed by a distributed system's structure and those impo...
Abstract. This text is an informal review of several randomized algorithms that have appeared over the past two decades and have proved instrumental in extracting efficiently quant...
Similarity search methods are widely used as kernels in various data mining and machine learning applications including those in computational biology, web search/clustering. Near...