Database Paper Browser

Back to papers

Better Sliding Window Algorithms to Maximize Subadditive and Diversity Objectives

Summary: Introduces a general method for sliding-window streaming maximization that bypasses exponential/smooth-histogram limits to achieve sublinear space and update time. Instantiated for submodular, diversity and subadditive objectives with cardinality constraints, improving prior problem-specific bounds. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
1763
Venue
PODS
Year
2019
Pagerank
4.9383139e-05
Overall Rank
6,755 | 53.01%
DOI
10.1145/3294052.3319701

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank Citing Paper Year Venue Pagerank
8,677 On Reporting Durable Patterns in Temporal Proximity Graphs 2024 PODS 4.4703012e-05
Previous Page 1 / 1 Next

Outgoing Citations (Sorted by Pagerank)

Showing 8 of 8 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Previous Page 1 / 1 Next

Semantically Similar Papers