most citedPhylogeny-informed fitness estimation

3 citations · 6 across the 5 of their papers we have counts for

collaborators

5 papers

cs.NE2024

On the Robustness of Lexicase Selection to Contradictory Objectives

Shakiba Shahbandegan, Emily Dolson

Lexicase and epsilon-lexicase selection are state of the art parent selection techniques for problems featuring multiple selection criteria. Originally, lexicase selection was deve…

cs.DS20242 cited

Analysis of Phylogeny Tracking Algorithms for Serial and Multiprocess Applications

Matthew Andres Moreno, Santiago Rodriguez Papa, Emily Dolson

Since the advent of modern bioinformatics, the challenging, multifaceted problem of reconstructing phylogenetic history from biological sequences has hatched perennial statistical…

cs.DS2024

Algorithms for Efficient, Compact Online Data Stream Curation

Matthew Andres Moreno, Santiago Rodriguez Papa, Emily Dolson

Data stream algorithms tackle operations on high-volume sequences of read-once data items. Data stream scenarios include inherently real-time systems like sensor networks and finan…

cs.NE20241 cited

Runtime phylogenetic analysis enables extreme subsampling for test-based problems

Alexander Lalejini, Marcos Sanson, Jack Garbus +2

A phylogeny describes the evolutionary history of an evolving population. Evolutionary search algorithms can perfectly track the ancestry of candidate solutions, illuminating a pop…

cs.NE20233 cited

Phylogeny-informed fitness estimation

Alexander Lalejini, Matthew Andres Moreno, Jose Guadalupe Hernandez +1

Phylogenies (ancestry trees) depict the evolutionary history of an evolving population. In evolutionary computing, a phylogeny can reveal how an evolutionary algorithm steers a pop…