Recent works proposed various linear self-attention mechanisms, scaling only asO(L)for serial computation. We conduct a thorough complexity analysis of Performers,aclass which includes most recent linear Transformer mechanisms.

In a setting with multiple buyers, a buyer's expected value for an experiment may

The main question about the spiked Wigner model is: how large should the signal-to-noise ratio λ > 0 be in order to achieve constant correlation withx?

What makes a classifier have the ability to generalize? There have been a lot of important attempts to address this question, but a clear answer is still elusive.

Indeedin learning applications, where symmetric tensors areformed from statistical moments (higher-order covariances) or multivariate derivatives (higher-order Hessians), CP decomposition has enabled parameter estimation for mixtures of Gaussians [20, 35], generalized linear models [34], shallow neuralnetworks[19,24,42],deepernetworks[17,18,30],hiddenMarkovmodels[5],amongothers.