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20172020
most cited"Bring Your Own Greedy"+Max: Near-Optimal -Approximations for Submodular Knapsack

9 citations · 17 across the 6 of their papers we have counts for

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cs.DS20202 cited

Sensitivity Analysis of the Maximum Matching Problem

Yuichi Yoshida, Samson Zhou

We consider the sensitivity of algorithms for the maximum matching problem against edge and vertex modifications. Algorithms with low sensitivity are desirable because they are rob…

cs.DS2019

Fast Fourier Sparsity Testing

Grigory Yaroslavtsev, Samson Zhou

A function is -sparse if it has at most non-zero Fourier coefficients. Motivated by applications to fast sparse Fourier transforms over $…

cs.DS20199 cited

"Bring Your Own Greedy"+Max: Near-Optimal -Approximations for Submodular Knapsack

Dmitrii Avdiukhin, Grigory Yaroslavtsev, Samson Zhou

The problem of selecting a small-size representative summary of a large dataset is a cornerstone of machine learning, optimization and data science. Motivated by applications to re…

cs.DS2019

Approximate -Sketching of Valuation Functions

Grigory Yaroslavtsev, Samson Zhou

We study the problem of constructing a linear sketch of minimum dimension that allows approximation of a given real-valued function

cs.DS2019

Adversarially Robust Submodular Maximization under Knapsack Constraints

Dmitrii Avdiukhin, Slobodan Mitrović, Grigory Yaroslavtsev +1

We propose the first adversarially robust algorithm for monotone submodular maximization under single and multiple knapsack constraints with scalable implementations in distributed…

cs.DS20176 cited

Optimal Parametric Search for Path and Tree Partitioning

Greg N. Frederickson, Samson Zhou

We present linear-time algorithms for partitioning a path or a tree with weights on the vertices by removing edges to maximize the minimum-weight component. We also use the sam…