Clustering in point processes on linear networks using nearest neighbour volumes
Sign Up to like & getrecommendations! Published in 2024 at "Journal of Applied Statistics"
DOI: 10.1080/02664763.2024.2411214
Abstract: This study introduces a novel method specifically designed to detect clusters of points within linear networks. This method extends a classification approach used for point processes in spatial contexts. Unlike traditional methods that operate on… read more here.
Keywords: linear networks; neighbour volumes; point processes; nearest neighbour ... See more keywords
Multi-Sender Index Coding Over Linear Networks
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Communications Letters"
DOI: 10.1109/lcomm.2021.3132988
Abstract: We consider an index coding problem in which several transmitters deliver distinct files to a number of users with minimum delay. Each user has access to a subset of other files from the library, which… read more here.
Keywords: index coding; index; coding linear; multi sender ... See more keywords
The loss surface of deep linear networks viewed through the algebraic geometry lens
Sign Up to like & getrecommendations! Published in 2021 at "IEEE transactions on pattern analysis and machine intelligence"
DOI: 10.1109/tpami.2021.3071289
Abstract: By using the viewpoint of modern computational algebraic geometry, we explore properties of the optimization landscapes of the deep linear neural network models. After clarifying on the various definitions of "flat" minima, we show that… read more here.
Keywords: algebraic geometry; number; linear networks; minima ... See more keywords
Kriging models for linear networks and nonâEuclidean distances: Cautions and solutions
Sign Up to like & getrecommendations! Published in 2018 at "Methods in Ecology and Evolution"
DOI: 10.1111/2041-210x.12979
Abstract: There are now several examples in the ecological literature where, for spatial prediction like kriging, non-Euclidean distances were used in autocorrelation models developed under a Euclidean distance assumption. This leads to a problem where prediction… read more here.
Keywords: linear networks; euclidean distances; networks non; models linear ... See more keywords