Makarychev, Konstantin

15 publications

NeurIPS 2025 Dynamic Algorithm for Explainable $k$-Medians Clustering Under $\ell_p$ Norm Konstantin Makarychev, Ilias Papanikolaou, Liren Shan
ICML 2025 Sparse-Pivot: Dynamic Correlation Clustering for Node Insertions Mina Dalirrooyfard, Konstantin Makarychev, Slobodan Mitrović
AAAI 2024 Approximation Scheme for Weighted Metric Clustering via Sherali-Adams Dmitrii Avdiukhin, Vaggos Chatziafratis, Konstantin Makarychev, Grigory Yaroslavtsev
ICML 2024 Pruned Pivot: Correlation Clustering Algorithm for Dynamic, Parallel, and Local Computation Models Mina Dalirrooyfard, Konstantin Makarychev, Slobodan Mitrovic
NeurIPS 2023 Random Cuts Are Optimal for Explainable K-Medians Konstantin Makarychev, Liren Shan
NeurIPS 2023 Single-Pass Pivot Algorithm for Correlation Clustering. Keep It Simple! Konstantin Makarychev, Sayak Chakrabarty
ICML 2021 Local Correlation Clustering with Asymmetric Classification Errors Jafar Jafarov, Sanchit Kalhan, Konstantin Makarychev, Yury Makarychev
ICML 2021 Near-Optimal Algorithms for Explainable K-Medians and K-Means Konstantin Makarychev, Liren Shan
AISTATS 2020 Bisect and Conquer: Hierarchical Clustering via Max-Uncut Bisection Vaggos Chatziafratis, Grigory Yaroslavtsev, Euiwoong Lee, Konstantin Makarychev, Sara Ahmadian, Alessandro Epasto, Mohammad Mahdian
ICML 2020 Correlation Clustering with Asymmetric Classification Errors Jafar Jafarov, Sanchit Kalhan, Konstantin Makarychev, Yury Makarychev
NeurIPS 2020 Improved Guarantees for K-Means++ and K-Means++ Parallel Konstantin Makarychev, Aravind Reddy, Liren Shan
NeurIPS 2019 Correlation Clustering with Local Objectives Sanchit Kalhan, Konstantin Makarychev, Timothy Zhou
NeurIPS 2017 Clustering Billions of Reads for DNA Data Storage Cyrus Rashtchian, Konstantin Makarychev, Miklos Racz, Siena Ang, Djordje Jevdjic, Sergey Yekhanin, Luis Ceze, Karin Strauss
COLT 2016 Learning Communities in the Presence of Errors Konstantin Makarychev, Yury Makarychev, Aravindan Vijayaraghavan
COLT 2015 Correlation Clustering with Noisy Partial Information Konstantin Makarychev, Yury Makarychev, Aravindan Vijayaraghavan