53 citations · 315 across the 37 of their papers we have counts for
6 papers · 1 filter
Time/Accuracy Tradeoffs for Learning a ReLU with respect to Gaussian Marginals
Surbhi Goel, Sushrut Karmalkar, Adam Klivans
We consider the problem of computing the best-fitting ReLU with respect to square-loss on a training set when the examples have been drawn according to a spherical Gaussian distrib…
Learning Restricted Boltzmann Machines with Arbitrary External Fields
Surbhi Goel
We study the problem of learning graphical models with latent variables. We give the first algorithm for learning locally consistent (ferromagnetic or antiferromagnetic) Restricted…
Learning Mixtures of Graphs from Epidemic Cascades
Jessica Hoffmann, Soumya Basu, Surbhi Goel +1
We consider the problem of learning the weighted edges of a balanced mixture of two undirected graphs from epidemic cascades. While mixture models are popular modeling tools, algor…
Recovering the Lowest Layer of Deep Networks with High Threshold Activations
Surbhi Goel, Rina Panigrahy
Giving provable guarantees for learning neural networks is a core challenge of machine learning theory. Most prior work gives parameter recovery guarantees for one hidden layer net…
Quantifying Perceptual Distortion of Adversarial Examples
Matt Jordan, Naren Manoj, Surbhi Goel +1
Recent work has shown that additive threat models, which only permit the addition of bounded noise to the pixels of an image, are insufficient for fully capturing the space of impe…
Learning Ising Models with Independent Failures
Surbhi Goel, Daniel M. Kane, Adam R. Klivans
We give the first efficient algorithm for learning the structure of an Ising model that tolerates independent failures; that is, each entry of the observed sample is missing with s…