The need to deal with massive data sets in many practical applications has led to a growing interest in computational models appropriate for large inputs. The most important quali...
We consider the problem of efficiently sampling Web search engine query results. In turn, using a small random sample instead of the full set of results leads to efficient approxi...
Aris Anagnostopoulos, Andrei Z. Broder, David Carm...
The massive data streams observed in network monitoring, data processing and scientific studies are typically too large to store. For many applications over such data, we must ob...
We present fault localization techniques suitable for diagnosing end-to-end service problems in communication systems with complex topologies. We refine a layered system model th...
We study the NP-complete TARGET SET SELECTION (TSS) problem occurring in social network analysis. Complementing results on its approximability and extending results for its restric...