18 citations · 38 across the 9 of their papers we have counts for
4 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…
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: \{-…
Inapproximability for Local Correlation Clustering and Dissimilarity Hierarchical Clustering
Vaggos Chatziafratis, Neha Gupta, Euiwoong Lee
We present hardness of approximation results for Correlation Clustering with local objectives and for Hierarchical Clustering with dissimilarity information. For the former, we stu…
Active Local Learning
Arturs Backurs, Avrim Blum, Neha Gupta
In this work we consider active local learning: given a query point , and active access to an unlabeled training set , output the prediction of a near-optimal $h \in H…