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Popular decision tree algorithms are provably noise tolerant



Guy Blanc , Jane Lange , Ali Malik , Li-Yang Tan

* Proceedings of the 39 th International Conference on Machine Learning, Baltimore, Maryland, USA, PMLR 162, 2022 

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On the power of adaptivity in statistical adversaries



Guy Blanc , Jane Lange , Ali Malik , Li-Yang Tan


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Provably efficient, succinct, and precise explanations



Guy Blanc , Jane Lange , Li-Yang Tan


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Properly learning decision trees in almost polynomial time



Guy Blanc , Jane Lange , Mingda Qiao , Li-Yang Tan

* 21 pages, to appear in FOCS 2021 

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Decision tree heuristics can fail, even in the smoothed setting



Guy Blanc , Jane Lange , Mingda Qiao , Li-Yang Tan

* To appear in RANDOM 2021 

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Learning stochastic decision trees



Guy Blanc , Jane Lange , Li-Yang Tan

* To appear in ICALP 2021 

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Testing and reconstruction via decision trees



Guy Blanc , Jane Lange , Li-Yang Tan


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Estimating decision tree learnability with polylogarithmic sample complexity



Guy Blanc , Neha Gupta , Jane Lange , Li-Yang Tan

* 25 pages, to appear in NeurIPS 2020 

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Universal guarantees for decision tree induction via a higher-order splitting criterion



Guy Blanc , Neha Gupta , Jane Lange , Li-Yang Tan


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Provable guarantees for decision tree induction: the agnostic setting



Guy Blanc , Jane Lange , Li-Yang Tan

* 20 pages, to appear in ICML 2020 

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