We consider the $ k $-clustering problem with $\ell_p $-norm cost, which includes $ k $-
median, $ k $-means and $ k $-center, under an individual notion of fairness proposed by …

This paper studies the fair range clustering problem in which the data points are from
different demographic groups and the goal is to pick $ k $ centers with the minimum …

Given a weighted set S of n elements, weighted set sampling (WSS) samples an element in
S so that each element ai; is sampled with a probability proportional to its weight w (ai). The …

Unlike a reporting query that returns all the elements satisfying a predicate, query sampling
returns only a sample set of those elements and has long been recognized as an important …

Similarity search is a fundamental algorithmic primitive, widely used in many computer
science disciplines. Given a set of points S and a radius parameter r> 0, the rnear neighbor …

Many applications require efficient management of large sets of intervals because many
objects are associated with intervals (eg, time and price intervals). In such interval …

The problem of inner product search (IPS) is important in many fields. Although maximum
inner product search (MIPS) is often considered, its result is usually skewed and static …

Semi-supervised classification methods are specialized to use a very limited amount of
labeled data for training and ultimately for assigning labels to the vast majority of unlabeled …

Similarity search is a fundamental algorithmic primitive, widely used in many computer
science disciplines. Given a set of points S and a radius parameter r> 0, the r-near neighbor …

Hashmap is a fundamental data structure in computer science. There has been extensive
research on constructing hashmaps that minimize the number of collisions leading to …