May 1, 2021 · We will give the first provably robust and computationally efficient methods for learning the parameters of a high-dimensional Gaussian, as well ...
May 1, 2021 · We give the first efficient algorithm for estimating the parameters of a high-dimensional Gaussian that is able to tolerate a constant fraction of corruptions.
Apr 26, 2021 · Robustness against adversarial attacks has recently been at the forefront of algorithmic design for machine learning tasks. In the adversarial ...
Part I: Introduction. • Robust Estimation in One-dimension. • Robustness vs. Hardness in High-dimensions. • Recent Results.
In this talk, we give the first efficient algorithm for estimating the parameters of a high-dimensional Gaussian which is able to tolerate a constant fraction ...
In this tutorial, we will survey the exciting recent progress in algorithmic robust statistics. We will give the first provably robust and efficiently ...
Part I: Introduction. • Robust Estimation in One-dimension. • Robustness vs. Hardness in High-dimensions. • Our Results. Part II: Agnostically Learning a ...
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Part I: Introduction. • Robust Estimation in One-dimension. • Robustness vs. Hardness in High-dimensions. • Our Results. Part II: Agnostically Learning a ...
Oct 17, 2023 · Algorithmic robustness refers to the sustained performance of a computational system in the face of change in the nature of the environment.
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Research Highlights: Robustness meets Algorithms – IFDS
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Jun 11, 2021 · The article presents a high-level description of groundbreaking work by the authors, which developed the first robust learning algorithms for high-dimensional ...