Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Sliding Window Algorithms for k-Clustering Problems   The sliding window model of computation captures scenarios in which data is
arriving continuously, but only the latest $w$ elements should be used for
analysis. The goal is to design algorithms that update the solution efficiently
with each arrival rather than recomputing it from scratch. In this work, we
focus on $k$-clustering problems such as $k$-means and $k$-median. In this
setting, we provide simple and practical algorithms that offer stronger
performance guarantees than previous results. Empirically, we show that our
methods store only a small fraction of the data, are orders of magnitude
faster, and find solutions with costs only slightly higher than those returned
by algorithms with access to the full dataset.

18
The categories of this paper are: econ
37
The categories of this paper are: supr-con
27
The categories of this paper are: comp-gas
35
The categories of this paper are: mtrl-th
17
The categories of this paper are: q-fin
26
The categories of this paper are: bayes-an
24
The categories of this paper are: dg-ga
6
The categories of this paper are: astro-ph
25
The categories of this paper are: patt-sol
13
The categories of this paper are: quant-ph
28
The categories of this paper are: alg-geom
34
The categories of this paper are: chem-ph
30
The categories of this paper are: q-alg
22
The categories of this paper are: chao-dyn
14
The categories of this paper are: math-ph
10
The categories of this paper are: q-bio