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20202022
most citedRun2Survive: A Decision-theoretic Approach to Algorithm Selection based on Survival Analysis

6 citations · 8 across the 6 of their papers we have counts for

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cs.LG20221 cited

HARRIS: Hybrid Ranking and Regression Forests for Algorithm Selection

Lukas Fehring, Jonas Hanselle, Alexander Tornede

It is well known that different algorithms perform differently well on an instance of an algorithmic problem, motivating algorithm selection (AS): Given an instance of an algorithm…

cs.LG2021

Machine Learning for Online Algorithm Selection under Censored Feedback

Alexander Tornede, Viktor Bengs, Eyke Hüllermeier

In online algorithm selection (OAS), instances of an algorithmic problem class are presented to an agent one after another, and the agent has to quickly select a presumably best al…

cs.LG2021

Algorithm Selection on a Meta Level

Alexander Tornede, Lukas Gehring, Tanja Tornede +2

The problem of selecting an algorithm that appears most suitable for a specific instance of an algorithmic problem class, such as the Boolean satisfiability problem, is called inst…

cs.LG2020

Towards Meta-Algorithm Selection

Alexander Tornede, Marcel Wever, Eyke Hüllermeier

Instance-specific algorithm selection (AS) deals with the automatic selection of an algorithm from a fixed set of candidates most suitable for a specific instance of an algorithmic…

cs.LG20206 cited

Run2Survive: A Decision-theoretic Approach to Algorithm Selection based on Survival Analysis

Alexander Tornede, Marcel Wever, Stefan Werner +2

Algorithm selection (AS) deals with the automatic selection of an algorithm from a fixed set of candidate algorithms most suitable for a specific instance of an algorithmic problem…

cs.LG2020

Extreme Algorithm Selection With Dyadic Feature Representation

Alexander Tornede, Marcel Wever, Eyke Hüllermeier

Algorithm selection (AS) deals with selecting an algorithm from a fixed set of candidate algorithms most suitable for a specific instance of an algorithmic problem, e.g., choosing…