1 citations · 2 across the 34 of their papers we have counts for
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Testable Learning of General Halfspaces under Massart Noise
Ilias Diakonikolas, Giannis Iakovidis, Daniel M. Kane +1
We study the algorithmic task of testably learning general Massart halfspaces under the Gaussian distribution. In the testable learning setting, the aim is the design of a tester-l…
PTF Testing Lower Bounds for Non-Gaussian Component Analysis
Ilias Diakonikolas, Daniel M. Kane, Sihan Liu +1
This work studies information-computation gaps for statistical problems. A common approach for providing evidence of such gaps is to show sample complexity lower bounds (that are s…
Information-Computation Tradeoffs for Noiseless Linear Regression with Oblivious Contamination
Ilias Diakonikolas, Chao Gao, Daniel M. Kane +2
We study the task of noiseless linear regression under Gaussian covariates in the presence of additive oblivious contamination. Specifically, we are given i.i.d.\ samples from a di…
Linear Regression under Missing or Corrupted Coordinates
Ilias Diakonikolas, Jelena Diakonikolas, Daniel M. Kane +2
We study multivariate linear regression under Gaussian covariates in two settings, where data may be erased or corrupted by an adversary under a coordinate-wise budget. In the inco…
On Fine-Grained Distinct Element Estimation
Ilias Diakonikolas, Daniel M. Kane, Jasper C. H. Lee +3
We study the problem of distributed distinct element estimation, where servers each receive a subset of a universe and aim to compute a -approximation to…
SoS Certificates for Sparse Singular Values and Their Applications: Robust Statistics, Subspace Distortion, and More
Ilias Diakonikolas, Samuel B. Hopkins, Ankit Pensia +1
We study for random rectangular matrices. If is an matrix with independent Gaussian entries, we give a new family of…
Super Non-singular Decompositions of Polynomials and their Application to Robustly Learning Low-degree PTFs
Ilias Diakonikolas, Daniel M. Kane, Vasilis Kontonis +2
We study the efficient learnability of low-degree polynomial threshold functions (PTFs) in the presence of a constant fraction of adversarial corruptions. Our main algorithmic resu…