Learned probing cardinality estimation for high-dimensional approximate NN search
Approximate nearest neighbor (ANN) search in high-dimensional space plays an essential
role in a variety of real-world applications. A well-known solution to ANN search, inverted file …
role in a variety of real-world applications. A well-known solution to ANN search, inverted file …
Learning-based query optimization for multi-probe approximate nearest neighbor search
Approximate nearest neighbor search (ANNS) is a fundamental problem that has attracted
widespread attention for decades. Multi-probe ANNS is one of the most important classes of …
widespread attention for decades. Multi-probe ANNS is one of the most important classes of …
Consistent and flexible selectivity estimation for high-dimensional data
Selectivity estimation aims at estimating the number of database objects that satisfy a
selection criterion. Answering this problem accurately and efficiently is essential to many …
selection criterion. Answering this problem accurately and efficiently is essential to many …