Schedule

Monday

9:00 - 9:30 Samir Khuller: Old result on Clustering with Open Problems

9:30 - 10:00 Yuval Rabani: Min-Sum Clustering

10:00 - 10:30 Break

10:30 - 11:00 Anupam Gupta: Nearly Tight Bounds for Explainable Clustering

11:00 - 11:30 Chris Schwiegelshohn: Beyond Worst Case Analysis for Coresets

11:30 - 14:00 Lunch Break

14:00 - 15:00 Deeparnab Chakrabarty: Round-or-Cut Technique for designing Approximation Algorithms for Clustering Problems

15:00 - 15:30 Soheil Behnezhad: Clustering Massive Data: Lessons from Sublinear Time Graph Algorithms

Tuesday

9:00 - 10:00 Jakub Łącki: Hierarchical agglomerative clustering: highly scalable algorithms and lower bounds

10:00 - 10:30 Break

10:30 - 11:00 Aditya Anand: Separating k-Median from the Supplier Version

11:00 - 11:30 Jarek Byrka: An O(loglog n)-Approximation for Submodular Facility Location

11:30 - 12:00 Alma Ghafari: Sublinear Algorithm for Correlation Clustering: Beyond Pivot

12:00 - 14:00 Lunch Break

14:00 - 15:00 Yury Makarychev: Fair Representation and Socially Fair Clustering

15:00 - 15:30 Samson Zhou: Near-Optimal k-Clustering in the Sliding Window Model

Wednesday

9:00 - 9:30 Evangelos Chatziafratis: From Hierarchical Clustering to Phylogenetic CSPs

9:30 - 10:00 Konstantin Makarychev: Pruned Pivot: Correlation Clustering Algorithm for Streaming, Dynamic, Parallel, and Local Computation Models

10:00 - 10:30 Break

10:30 - 11:00 David Woodruff: Streaming Euclidean k-median and k-means with o(log n) Words of Memory

11:00 - 11:30 Annika Hennes: Faster Query Times for Fully Dynamic k-Center Clustering with Outliers

11:30 - 12:00 Liren Shan: Random Cuts are Optimal for Explainable k-Medians