Zobrazeno 1 - 10
of 155
pro vyhledávání: '"Anthony Wirth"'
Publikováno v:
Proceedings of the 41st ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems.
Longitudinal data tracking under Local Differential Privacy (LDP) is a challenging task. Baseline solutions that repeatedly invoke a protocol designed for one-time computation lead to linear decay in the privacy or utility guarantee with respect to t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::64d0123f4d9a53378f99c314d8967172
https://doi.org/10.1145/3517804.3526226
https://doi.org/10.1145/3517804.3526226
Publikováno v:
Proceedings of the 2022 ACM on Asia Conference on Computer and Communications Security.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e424c88639f7548293661f6bfd991d95
https://doi.org/10.1145/3488932.3497761
https://doi.org/10.1145/3488932.3497761
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030997359
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7be214dce42f4697fb8b1cf3e1a016f1
https://doi.org/10.1007/978-3-030-99736-6_11
https://doi.org/10.1007/978-3-030-99736-6_11
Publikováno v:
SIGMOD Conference
Structural Clustering ($DynClu$) is one of the most popular graph clustering paradigms. In this paper, we consider $StrClu$ under two commonly adapted similarities, namely Jaccard similarity and cosine similarity on a dynamic graph, $G = \langle V, E
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::90c6f11d69f53ee297829133b898e98c
https://doi.org/10.1145/3448016.3452828
https://doi.org/10.1145/3448016.3452828
Publikováno v:
KDD
Motivated by applications in community detection and dense subgraph discovery, we consider new clustering objectives in hypergraphs and bipartite graphs. These objectives are parameterized by one or more resolution parameters in order to enable diver
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c0ce4a559e81327de57a5c191466084c
http://arxiv.org/abs/2002.09460
http://arxiv.org/abs/2002.09460
Publikováno v:
WWW
Finding clusters of well-connected nodes in a graph is an extensively studied problem in graph-based data analysis. Because of its many applications, a large number of distinct graph clustering objective functions and algorithms have already been pro
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::36da8cc0978eb6ef840e1739b43e8327
http://arxiv.org/abs/1903.05246
http://arxiv.org/abs/1903.05246
Publikováno v:
ICML
Algorithmica
Proceedings of the 32nd International Conference on Machine Learning
Algorithmica
Proceedings of the 32nd International Conference on Machine Learning
Clustering is a fundamental tool for analyzing large data sets. A rich body of work has been devoted to designing data-stream algorithms for the relevant optimization problems such as k-center, k-median, and k-means. Such algorithms need to be both t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c75ea8af5479c16651f67ca4b22aefe4
http://arxiv.org/abs/1812.02023
http://arxiv.org/abs/1812.02023
Publikováno v:
WWW
Graph clustering, or community detection, is the task of identifying groups of closely related objects in a large network. In this paper we introduce a new community detection framework called LambdaCC that is based on a specially weighted version of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::811097ddc86a2418d16085a3baa0e499
https://doi.org/10.1145/3178876.3186110
https://doi.org/10.1145/3178876.3186110
Publikováno v:
WWW
Correlation clustering is a technique for aggregating data based on qualitative information about which pairs of objects are labeled `similar' or `dissimilar.' Because the optimization problem is NP-hard, much of the previous literature focuses on fi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::27e390ca4e9d1199c2c4550cc97d73a4
https://doi.org/10.1145/3038912.3052586
https://doi.org/10.1145/3038912.3052586
Publikováno v:
WSDM
Vast amounts of data are collected and stored every day, as part of corporate knowledge bases and as a response to legislative compliance requirements. To reduce the cost of retaining such data, compression tools are often applied. But simply seeking
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::629efd93f71577f504b634a7bb001471
https://doi.org/10.1145/3018661.3018738
https://doi.org/10.1145/3018661.3018738