2 citations · 2 across the 2 of their papers we have counts for
2 papers
cs.LG2022
The computational complexity of some explainable clustering problems
Eduardo Sany Laber
We study the computational complexity of some explainable clustering problems in the framework proposed by [Dasgupta et al., ICML 2020], where explainability is achieved via axis-a…
cs.DS2014★ 2 cited
Trading off Worst and Expected Cost in Decision Tree Problems and a Value Dependent Model
Aline Saettler, Eduardo Laber, Ferdinando Cicalese
We study the problem of evaluating a discrete function by adaptively querying the values of its variables until the values read uniquely determine the value of the function. Readin…