Approximation Algorithm : k-Median

Statistical Centrality Measures, Facility Location & Voronoi Games by Professor Bhaswar BhattacharyaПодробнее

Fully Dynamic k-Median with Near-Optimal Update Time and Recourse [STOC'25]Подробнее

Lesson 19: Network Algorithms and Approximations by Mohammad Hajiaghayi: k-Center and k-MedianПодробнее

Approximation Algorithm : Local Search : l-Median, Max 2-SAT by saket saurabhПодробнее

FOCS 2024 1C Fully Dynamic k-Clustering with Fast Update Time and Small RecourseПодробнее

Robert Krauthgamer - Fully Scalable MPC Algorithms for Clustering in High DimensionПодробнее

Socially Fair and Fair Representation ClusteringПодробнее

Separating k-Median from the Supplier VersionПодробнее

Streaming Euclidean k-median and k-means with o(log n) SpaceПодробнее

Random Cuts are Optimal for Explainable k-MediansПодробнее

Fully Dynamic k-Clustering in Õ(k) Update Time [NeurIPS23]Подробнее

k Medians in 60 Seconds | Machine Learning AlgorithmsПодробнее

Streaming Euclidean k-median and k-means with o(log n) SpaceПодробнее

APPROX: Ordered k Median with OutliersПодробнее

Fair Representation Clustering with Several Protected ClassesПодробнее

Fair Representation Clustering with Several Protected ClassesПодробнее

STOC 2022 - Improved Approximations for Euclidean k-Means and k-MedianПодробнее

IDEAL Workshop: Eden Chlamtáč, Approximating Fair Clustering with Cascaded Norm ObjectivesПодробнее

IDEAL Workshop: Liren Shan, Explainable k-means. Don’t be greedy, plant bigger trees!Подробнее