1 citations · 2 across the 30 of their papers we have counts for
8 papers · 1 filter
Active Learning of General Halfspaces: Label Queries vs Membership Queries
Ilias Diakonikolas, Daniel M. Kane, Mingchen Ma
We study the problem of learning general (i.e., not necessarily homogeneous) halfspaces under the Gaussian distribution on in the presence of some form of query access. In th…
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…
Efficient Testable Learning of General Halfspaces with Adversarial Label Noise
Ilias Diakonikolas, Daniel M. Kane, Sihan Liu +1
We study the task of testable learning of general -- not necessarily homogeneous -- halfspaces with adversarial label noise with respect to the Gaussian distribution. In the testab…
Replicability in High Dimensional Statistics
Max Hopkins, Russell Impagliazzo, Daniel Kane +2
The replicability crisis is a major issue across nearly all areas of empirical science, calling for the formal study of replicability in statistics. Motivated in this context, [Imp…
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…
Robust Sparse Estimation for Gaussians with Optimal Error under Huber Contamination
Ilias Diakonikolas, Daniel M. Kane, Sushrut Karmalkar +2
We study Gaussian sparse estimation tasks in Huber's contamination model with a focus on mean estimation, PCA, and linear regression. For each of these tasks, we give the first sam…
SQ Lower Bounds for Non-Gaussian Component Analysis with Weaker Assumptions
Ilias Diakonikolas, Daniel Kane, Lisheng Ren +1
We study the complexity of Non-Gaussian Component Analysis (NGCA) in the Statistical Query (SQ) model. Prior work developed a general methodology to prove SQ lower bounds for this…
Statistical Query Lower Bounds for Learning Truncated Gaussians
Ilias Diakonikolas, Daniel M. Kane, Thanasis Pittas +1
We study the problem of estimating the mean of an identity covariance Gaussian in the truncated setting, in the regime when the truncation set comes from a low-complexity family $\…