8 citations · 18 across the 18 of their papers we have counts for
5 papers · 1 filter
Estimating decision tree learnability with polylogarithmic sample complexity
Guy Blanc, Neha Gupta, Jane Lange +1
We show that top-down decision tree learning heuristics are amenable to highly efficient learnability estimation: for monotone target functions, the error of the decision tree hypo…
Query strategies for priced information, revisited
Guy Blanc, Jane Lange, Li-Yang Tan
We consider the problem of designing query strategies for priced information, introduced by Charikar et al. In this problem the algorithm designer is given a function $f : \{0,1\}^…
Universal guarantees for decision tree induction via a higher-order splitting criterion
Guy Blanc, Neha Gupta, Jane Lange +1
We propose a simple extension of top-down decision tree learning heuristics such as ID3, C4.5, and CART. Our algorithm achieves provable guarantees for all target functions $f: \{-…
Efficient hyperparameter optimization by way of PAC-Bayes bound minimization
John J. Cherian, Andrew G. Taube, Robert T. McGibbon +6
Identifying optimal values for a high-dimensional set of hyperparameters is a problem that has received growing attention given its importance to large-scale machine learning appli…
Provable guarantees for decision tree induction: the agnostic setting
Guy Blanc, Jane Lange, Li-Yang Tan
We give strengthened provable guarantees on the performance of widely employed and empirically successful {\sl top-down decision tree learning heuristics}. While prior works have f…