3 citations · 3 across the 8 of their papers we have counts for
5 papers · 1 filter
Identifying all snarls and superbubbles in linear-time, via a unified SPQR-tree framework
Francisco Sena, Aleksandr Politov, Corentin Moumard +4
Snarls and superbubbles are fundamental pangenome decompositions capturing variant sites. These bubble-like structures underpin key tasks in computational pangenomics, including st…
Scaling Up Bayesian DAG Sampling
Daniele Nikzad, Alexander Zhilkin, Juha Harviainen +3
Bayesian inference of Bayesian network structures is often performed by sampling directed acyclic graphs along an appropriately constructed Markov chain. We present two techniques…
Improving Decision Trees through the Lens of Parameterized Local Search
Juha Harviainen, Frank Sommer, Manuel Sorge
Algorithms for learning decision trees often include heuristic local-search operations such as (1) adjusting the threshold of a cut or (2) also exchanging the feature of that cut.…
Graph Reconstruction with a Connected Components Oracle
Juha Harviainen, Pekka Parviainen
In the Graph Reconstruction (GR) problem, the goal is to recover a hidden graph by utilizing some oracle that provides limited access to the structure of the graph. The interest is…
Optimal Decision Tree Pruning Revisited: Algorithms and Complexity
Juha Harviainen, Frank Sommer, Manuel Sorge +1
We present a comprehensive classical and parameterized complexity analysis of decision tree pruning operations, extending recent research on the complexity of learning small decisi…