From the 2 of 21 linked papers with an AI index.
8 papers · 1 filter
Linear Regression under Missing or Corrupted Coordinates
Ilias Diakonikolas, Jelena Diakonikolas, Daniel M. Kane +2
The paper analyzes multivariate linear regression with Gaussian features when an adversary can delete or corrupt a fraction of entries per coordinate, providing tight error bounds…
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…
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 t…
Implicit High-Order Moment Tensor Estimation and Learning Latent Variable Models
Ilias Diakonikolas, Daniel M. Kane
We study the task of learning latent-variable models. A common algorithmic technique for this task is the method of moments. Unfortunately, moment-based approaches are hampered by…