93 citations · 244 across the 16 of their papers we have counts for
4 papers · 1 filter
Directed Hamiltonicity and Out-Branchings via Generalized Laplacians
Andreas Björklund, Petteri Kaski, Ioannis Koutis
We are motivated by a tantalizing open question in exact algorithms: can we detect whether an -vertex directed graph has a Hamiltonian cycle in time significantly less than…
On Fully Dynamic Graph Sparsifiers
Ittai Abraham, David Durfee, Ioannis Koutis +2
We initiate the study of dynamic algorithms for graph sparsification problems and obtain fully dynamic algorithms, allowing both edge insertions and edge deletions, that take polyl…
Incremental Spectral Sparsification for Large-Scale Graph-Based Semi-Supervised Learning
Daniele Calandriello, Alessandro Lazaric, Michal Valko +1
While the harmonic function solution performs well in many semi-supervised learning (SSL) tasks, it is known to scale poorly with the number of samples. Recent successful and scala…
Scalable Constrained Clustering: A Generalized Spectral Method
Mihai Cucuringu, Ioannis Koutis, Sanjay Chawla +2
We present a simple spectral approach to the well-studied constrained clustering problem. It captures constrained clustering as a generalized eigenvalue problem with graph Laplacia…