7 citations · 29 across the 31 of their papers we have counts for
7 papers · 2 filters
Hedgegraph Polymatroids
Karthekeyan Chandrasekaran, Chandra Chekuri, Weihang Wang +1
Graphs and hypergraphs combine expressive modeling power with algorithmic efficiency for a wide range of applications. Hedgegraphs generalize hypergraphs further by grouping hypere…
-Separating Principal Partition Sequence of Submodular Functions
Kristóf Bérczi, Karthekeyan Chandrasekaran, Tamás Király +1
Narayanan showed the existence of the principal partition sequence of a submodular function, a structure with numerous applications in areas such as clustering, fast algorithms, an…
Hypergraph Splitting-Off via Element-Connectivity Preserving Reductions
Karthekeyan Chandrasekaran, Chandra Chekuri, Shubhang Kulkarni
Bérczi, Chandrasekaran, Király, and Kulkarni (ICALP 2024) recently described a splitting-off procedure in hypergraphs that preserves local-connectivity and outlined some applicatio…
Approximating Submodular Matroid-Constrained Partitioning
Kristóf Bérczi, Karthekeyan Chandrasekaran, Tamás Király +1
The submodular partitioning problem asks to minimize, over all partitions of a ground set , the sum of a given submodular function over the parts of . The problem has…
Minimum Cost Nowhere-zero Flows and Cut-balanced Orientations
Karthekeyan Chandrasekaran, Siyue Liu, R. Ravi
Flows and colorings are disparate concepts in graph algorithms -- the former is tractable while the latter is intractable. Tutte introduced the concept of nowhere-zero flows to uni…
Online Disjoint Spanning Trees and Polymatroid Bases
Karthekeyan Chandrasekaran, Chandra Chekuri, Weihao Zhu
Finding the maximum number of disjoint spanning trees in a given graph is a well-studied problem with several applications and connections. The Tutte-Nash-Williams theorem provides…
On Deleting Vertices to Reduce Density in Graphs and Supermodular Functions
Karthekeyan Chandrasekaran, Chandra Chekuri, Shubhang Kulkarni
We consider deletion problems in graphs and supermodular functions where the goal is to reduce density. In Graph Density Deletion (GraphDD), we are given a graph with non…