9 citations · 18 across the 8 of their papers we have counts for
8 papers
Fair Submodular Cover
Wenjing Chen, Shuo Xing, Samson Zhou +1
Submodular optimization is a fundamental problem with many applications in machine learning, often involving decision-making over datasets with sensitive attributes such as gender…
Learning-Augmented Search Data Structures
Chunkai Fu, Brandon G. Nguyen, Jung Hoon Seo +2
We study the integration of machine learning advice to improve upon traditional data structure designed for efficient search queries. Although there has been recent effort in impro…
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…
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 $…
"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…
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 …