Causal inference aims todrawacausal relationship between some treatment and targetresponses.

Model extraction attacks have renewed interest in the classic problem of learning neural networks from queries. This work gives the first polynomial-time algorithm for learning one hidden layer neural networks provided black-box access to the network.

For this, we utilize an implementationbyCroceandHein[2021],togetherwithlinearscaling(=10)ofthegradientinorder to balance the relative scale to random noise.