1 code implementation • 21 Jan 2022 • Xiaoyu Ma, Sylvain Sardy, Nick Hengartner, Nikolai Bobenko, Yen Ting Lin
To fit sparse linear associations, a LASSO sparsity inducing penalty with a single hyperparameter provably allows to recover the important features (needles) with high probability in certain regimes even if the sample size is smaller than the dimension of the input vector (haystack).
no code implementations • 2 Jun 2022 • Diane Oyen, Michal Kucer, Nick Hengartner, Har Simrat Singh
However, for the special case of class-dependent label noise (independent of features given the class label), the tipping point can be as low as 50%.