Dynamic network models and graphon estimation Page 1 The Annals of Statistics 2019, Vol.
47, No. 4, 2378–2403 https://doi.org/10.1214/18-AOS1751 © Institute of Mathematical …

State access in existing distributed stream processing systems is restricted locally within
each operator. However, in advanced stream analytics such as online learning and dynamic …

Graph learning is a prevalent domain that endeavors to learn the intricate relationships
among nodes and the topological structure of graphs. Over the years, graph learning has …

Temporal graphs abstractly model real-life inherently dynamic networks. Given a graph G, a
temporal graph with G as the underlying graph is a sequence of subgraphs (snapshots) G t …

The planted densest subgraph detection problem refers to the task of testing whether in a
given (random) graph there is a subgraph that is unusually dense. Specifically, we observe …

We study comparison sorting in the evolving data model, introduced by Anagnostopoulos,
Kumar, Mah-dian and Upfal (2011), where the true total order changes while the sorting …

Large text temporal collections provide insights into social and cultural change over time. To
quantify changes in topics in these corpora, embedding methods have been used as a …

We consider a variant of the planted clique problem where we are allowed unbounded
computational time but can only investigate a small part of the graph by adaptive edge …

We present an online community change detection algorithm called spectral CUSUM to
detect the emergence of a community using a subspace projection procedure based on a …

We consider random simple temporal graphs in which every edge of the complete graph Kn
appears once within the time interval [0, 1] independently and uniformly at random. Our main …