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Spectral Clustering Oracles in Sublinear Time
The main technical contribution is a sublinear time oracle that provides dot product access to the spectral embedding of $G$ by estimating distributions of short random walks from vertices in $G$.
Data Structures and Algorithms
Beyond $1/2$-Approximation for Submodular Maximization on Massive Data Streams
It is the first low-memory, single-pass algorithm that improves the factor $0. 5$, under the natural assumption that elements arrive in a random order.
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