no code implementations • 13 Mar 2024 • Theodor Misiakiewicz, Basil Saeed
Specifically, we establish in this setting a non-asymptotic deterministic approximation for the test error of KRR -- with explicit non-asymptotic bounds -- that only depends on the eigenvalues and the target function alignment to the eigenvectors of the kernel.
no code implementations • 29 Sep 2023 • Andrea Montanari, Feng Ruan, Basil Saeed, Youngtak Sohn
Working in the high-dimensional regime in which the number of features $p$, the number of samples $n$ and the input dimension $d$ (in the nonlinear featurization setting) diverge, with ratios of order one, we prove a universality result establishing that the asymptotic behavior is completely determined by the expected covariance of feature vectors and by the covariance between features and labels.
no code implementations • 17 Feb 2022 • Andrea Montanari, Basil Saeed
In particular, the asymptotics of these quantities can be computed $-$to leading order$-$ under a simpler model in which the feature vectors ${\boldsymbol x}_i$ are replaced by Gaussian vectors ${\boldsymbol g}_i$ with the same covariance.
no code implementations • ICML 2020 • Basil Saeed, Snigdha Panigrahi, Caroline Uhler
We consider distributions arising from a mixture of causal models, where each model is represented by a directed acyclic graph (DAG).
no code implementations • 20 Oct 2019 • Daniel Irving Bernstein, Basil Saeed, Chandler Squires, Caroline Uhler
We consider the task of learning a causal graph in the presence of latent confounders given i. i. d.~samples from the model.
no code implementations • 11 May 2019 • Ilker Yildirim, Basil Saeed, Grace Bennett-Pierre, Tobias Gerstenberg, Joshua Tenenbaum, Hyowon Gweon
The ability to estimate task difficulty is critical for many real-world decisions such as setting appropriate goals for ourselves or appreciating others' accomplishments.
no code implementations • 25 Jul 2017 • Ilker Yildirim, Tobias Gerstenberg, Basil Saeed, Marc Toussaint, Josh Tenenbaum
In Experiment~2, we asked participants online to judge whether they think the person in the lab used one or two hands.