10 citations · 53 across the 28 of their papers we have counts for
7 papers · 1 filter
Agnostically Learning Multi-index Models with Queries
Ilias Diakonikolas, Daniel M. Kane, Vasilis Kontonis +2
We study the power of query access for the task of agnostic learning under the Gaussian distribution. In the agnostic model, no assumptions are made on the labels and the goal is t…
Self-Directed Linear Classification
Ilias Diakonikolas, Vasilis Kontonis, Christos Tzamos +1
In online classification, a learner is presented with a sequence of examples and aims to predict their labels in an online fashion so as to minimize the total number of mistakes. I…
Near-Optimal Bounds for Learning Gaussian Halfspaces with Random Classification Noise
Ilias Diakonikolas, Jelena Diakonikolas, Daniel M. Kane +2
We study the problem of learning general (i.e., not necessarily homogeneous) halfspaces with Random Classification Noise under the Gaussian distribution. We establish nearly-matchi…
Information-Computation Tradeoffs for Learning Margin Halfspaces with Random Classification Noise
Ilias Diakonikolas, Jelena Diakonikolas, Daniel M. Kane +2
We study the problem of PAC learning -margin halfspaces with Random Classification Noise. We establish an information-computation tradeoff suggesting an inherent gap between the…
SQ Lower Bounds for Learning Bounded Covariance GMMs
Ilias Diakonikolas, Daniel M. Kane, Thanasis Pittas +1
We study the complexity of learning mixtures of separated Gaussians with common unknown bounded covariance matrix. Specifically, we focus on learning Gaussian mixture models (GMMs)…
Robustly Learning a Single Neuron via Sharpness
Puqian Wang, Nikos Zarifis, Ilias Diakonikolas +1
We study the problem of learning a single neuron with respect to the -loss in the presence of adversarial label noise. We give an efficient algorithm that, for a broad famil…
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…