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Kirill Simonov

7 accepted papers

2023

The Parameterized Complexity of Network Microaggregation

AAAI 2023technical

Microaggregation is a classical statistical disclosure control technique which requires the input data to be partitioned into clusters while adhering to specified size constraints. We provide novel exact algorithms and lower bounds for the task of microaggregating a given network while considering b…

Cited by 7SourcePDFScholar
2022

How to Find a Good Explanation for Clustering?

AAAI 2022technical

k-means and k-median clustering are powerful unsupervised machine learning techniques. However, due to complicated dependences on all the features, it is challenging to interpret the resulting cluster assignments. Moshkovitz, Dasgupta, Rashtchian, and Frost proposed an elegant model of explainable…

Cited by 40SourcePDFScholar
2022

The Complexity of k-Means Clustering when Little is Known

ICML 2022spotlight

In the area of data analysis and arguably even in machine learning as a whole, few approaches have been as impactful as the classical k-means clustering. Here, we study the complexity of k-means clustering in settings where most of the data is not known or simply irrelevant. To obtain a more fine-gr…

Cited by 7SourcePDFScholar
2021

Fixed-Parameter and Approximation Algorithms for PCA with Outliers

ICML 2021spotlight

PCA with Outliers is the fundamental problem of identifying an underlying low-dimensional subspace in a data set corrupted with outliers. A large body of work is devoted to the information-theoretic aspects of this problem. However, from the computational perspective, its complexity is still not wel…

Cited by 7SourcePDFScholar