activity
20202023
most citedAlgorithms and SQ Lower Bounds for PAC Learning One-Hidden-Layer ReLU Networks

10 citations · 52 across the 10 of their papers we have counts for

collaborators

9 papers

cs.LG2021

Learning General Halfspaces with General Massart Noise under the Gaussian Distribution

Ilias Diakonikolas, Daniel M. Kane, Vasilis Kontonis +2

We study the problem of PAC learning halfspaces on with Massart noise under the Gaussian distribution. In the Massart model, an adversary is allowed to flip the labe…

cs.LG20212 cited

Agnostic Proper Learning of Halfspaces under Gaussian Marginals

Ilias Diakonikolas, Daniel M. Kane, Vasilis Kontonis +2

We study the problem of agnostically learning halfspaces under the Gaussian distribution. Our main result is the {\em first proper} learning algorithm for this problem whose sample…

cs.LG20213 cited

The Optimality of Polynomial Regression for Agnostic Learning under Gaussian Marginals

Ilias Diakonikolas, Daniel M. Kane, Thanasis Pittas +1

We study the problem of agnostic learning under the Gaussian distribution. We develop a method for finding hard families of examples for a wide class of problems by using LP dualit…

cs.LG20209 cited

A Polynomial Time Algorithm for Learning Halfspaces with Tsybakov Noise

Ilias Diakonikolas, Daniel M. Kane, Vasilis Kontonis +2

We study the problem of PAC learning homogeneous halfspaces in the presence of Tsybakov noise. In the Tsybakov noise model, the label of every sample is independently flipped with…

cs.LG202010 cited

Near-Optimal SQ Lower Bounds for Agnostically Learning Halfspaces and ReLUs under Gaussian Marginals

Ilias Diakonikolas, Daniel M. Kane, Nikos Zarifis

We study the fundamental problems of agnostically learning halfspaces and ReLUs under Gaussian marginals. In the former problem, given labeled examples from an un…

cs.LG202010 cited

Algorithms and SQ Lower Bounds for PAC Learning One-Hidden-Layer ReLU Networks

Ilias Diakonikolas, Daniel M. Kane, Vasilis Kontonis +1

We study the problem of PAC learning one-hidden-layer ReLU networks with hidden units on under Gaussian marginals in the presence of additive label noise. For th…