8 citations · 17 across the 7 of their papers we have counts for
7 papers · 1 filter
Multitask Learning via Shared Features: Algorithms and Hardness
Konstantina Bairaktari, Guy Blanc, Li-Yang Tan +2
We investigate the computational efficiency of multitask learning of Boolean functions over the -dimensional hypercube, that are related by means of a feature representation of…
Provably efficient, succinct, and precise explanations
Guy Blanc, Jane Lange, Li-Yang Tan
We consider the problem of explaining the predictions of an arbitrary blackbox model : given query access to and an instance , output a small set of 's features that i…
Decision tree heuristics can fail, even in the smoothed setting
Guy Blanc, Jane Lange, Mingda Qiao +1
Greedy decision tree learning heuristics are mainstays of machine learning practice, but theoretical justification for their empirical success remains elusive. In fact, it has long…
Learning stochastic decision trees
Guy Blanc, Jane Lange, Li-Yang Tan
We give a quasipolynomial-time algorithm for learning stochastic decision trees that is optimally resilient to adversarial noise. Given an -corrupted set of uniform random sampl…
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: \{-…