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Yanhao Wang
Researcher at University of Helsinki
Publications - 12
Citations - 108
Yanhao Wang is an academic researcher from University of Helsinki. The author has contributed to research in topics: Set (abstract data type) & Tuple. The author has an hindex of 3, co-authored 12 publications receiving 39 citations. Previous affiliations of Yanhao Wang include National University of Singapore.
Papers
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Proceedings ArticleDOI
Efficient Sampling Algorithms for Approximate Temporal Motif Counting
TL;DR: This paper proposes a generic edge sampling algorithm for estimating the number of instances of any temporal motif and devise an improved EWS algorithm that hybridizes edge sampling with wedge sampling for counting temporal motifs with 3 vertices and 3 edges.
Proceedings ArticleDOI
Coresets for Minimum Enclosing Balls over Sliding Windows
TL;DR: This paper investigates the problem of maintaining a coreset to preserve the minimum enclosing ball (MEB) for a sliding window of points that are continuously updated in a data stream and proposes two novel algorithms, namely SWMEB andSWMEB+, to maintain coresets for MEB over the sliding window with constant approximation ratios.
Journal ArticleDOI
A survey of typical attributed graph queries
TL;DR: This paper proposes a taxonomy of attributed graph queries based on query inputs and outputs and summarizes the definitions of queries that fall into each category and presents a fine-grained classification of queries within each category by analyzing the semantics and algorithmic motivations behind these queries.
Proceedings ArticleDOI
Fair and Representative Subset Selection from Data Streams
TL;DR: This work considers the setting where data items in the stream belong to one of several disjoint groups and investigates the optimization problem with an additional fairness constraint that limits selection to a given number of items from each group, and proposes efficient algorithms for the fairness-aware variant of the streaming submodular maximization problem.
Proceedings ArticleDOI
Minimum Coresets for Maxima Representation of Multidimensional Data
TL;DR: In this article, the authors studied the problem of finding the minimum coreset of the smallest size for the maxima representation of a point set in a multidimensional data set.