2 citations · 3 across the 4 of their papers we have counts for
4 papers
Efficient Testable Learning of Halfspaces with Adversarial Label Noise
Ilias Diakonikolas, Daniel M. Kane, Vasilis Kontonis +2
We give the first polynomial-time algorithm for the testable learning of halfspaces in the presence of adversarial label noise under the Gaussian distribution. In the recently intr…
Near-Optimal Bounds for Testing Histogram Distributions
Clément L. Canonne, Ilias Diakonikolas, Daniel M. Kane +1
We investigate the problem of testing whether a discrete probability distribution over an ordered domain is a histogram on a specified number of bins. One of the most common tools…
Computational-Statistical Gaps in Reinforcement Learning
Daniel Kane, Sihan Liu, Shachar Lovett +1
Reinforcement learning with function approximation has recently achieved tremendous results in applications with large state spaces. This empirical success has motivated a growing…
Convergence and Sample Complexity of SGD in GANs
Vasilis Kontonis, Sihan Liu, Christos Tzamos
We provide theoretical convergence guarantees on training Generative Adversarial Networks (GANs) via SGD. We consider learning a target distribution modeled by a 1-layer Generator…