activity
20172021
most citedEfficient Algorithms for k-Regret Minimizing Sets

22 citations · 23 across the 3 of their papers we have counts for

collaborators

7 papers

cs.DS2021

Dynamic Enumeration of Similarity Joins

Pankaj K. Agarwal, Xiao Hu, Stavros Sintos +1

This paper considers enumerating answers to similarity-join queries under dynamic updates: Given two sets of points in , a metric , and a distance…

cs.DB20211 cited

Combining Aggregation and Sampling (Nearly) Optimally for Approximate Query Processing

Xi Liang, Stavros Sintos, Zechao Shang +1

Sample-based approximate query processing (AQP) suffers from many pitfalls such as the inability to answer very selective queries and unreliable confidence intervals when sample si…

cs.DB2021

Durable Top-K Instant-Stamped Temporal Records with User-Specified Scoring Functions

Junyang Gao, Stavros Sintos, Pankaj K. Agarwal +1

A way of finding interesting or exceptional records from instant-stamped temporal data is to consider their "durability," or, intuitively speaking, how well they compare with other…

cs.CG2021

The Maximum Exposure Problem

Neeraj Kumar, Stavros Sintos, Subhash Suri

Given a set of points and axis-aligned rectangles in the plane, a point is called \emph{exposed} if it lies outside all rectangles in . In…

cs.DB2019

Selecting Data to Clean for Fact Checking: Minimizing Uncertainty vs. Maximizing Surprise

Stavros Sintos, Pankaj K. Agarwal, Jun Yang

We study the optimization problem of selecting numerical quantities to clean in order to fact-check claims based on such data. Oftentimes, such claims are technically correct, but…

cs.DB2019

Learning to Sample: Counting with Complex Queries

Brett Walenz, Stavros Sintos, Sudeepa Roy +1

We study the problem of efficiently estimating counts for queries involving complex filters, such as user-defined functions, or predicates involving self-joins and correlated subqu…