We prove a strong composition theorem for junta complexity and show how ...
We show how any PAC learning algorithm that works under the uniform
dist...
Ensuring that analyses performed on a dataset are representative of the
...
In the certification problem, the algorithm is given a function f with
c...
We investigate the computational efficiency of multitask learning of Boo...
We design an algorithm for finding counterfactuals with strong theoretic...
The authors recently gave an n^O(loglog n) time membership query
algorit...
Using the framework of boosting, we prove that all impurity-based decisi...
We study the problem of certification: given queries to a function f :
{...
We study a fundamental question concerning adversarial noise models in
s...
We consider the problem of explaining the predictions of an arbitrary
bl...
We give an n^O(loglog n)-time membership query algorithm for properly
an...
Greedy decision tree learning heuristics are mainstays of machine learni...
We give a 0.5368-competitive algorithm for edge-weighted online bipartit...
We give a quasipolynomial-time algorithm for learning stochastic decisio...
We study sublinear and local computation algorithms for decision trees,
...
We show that top-down decision tree learning heuristics are amenable to
...
We consider the problem of designing query strategies for priced informa...
We propose a simple extension of top-down decision tree learning heurist...
Identifying optimal values for a high-dimensional set of hyperparameters...
We give strengthened provable guarantees on the performance of widely
em...
We give efficient deterministic algorithms for converting randomized que...
Consider the following heuristic for building a decision tree for a func...
We consider deep networks, trained via stochastic gradient descent to
mi...