Dot-product attention mechanism plays a crucial role in modern deep
arch...
Infinite width limit has shed light on generalization and optimization
a...
We propose an algorithm for robust recovery of the spherical harmonic
ex...
We give an input sparsity time sampling algorithm for spectrally
approxi...
We propose efficient random features for approximating a new and rich cl...
Computing the dominant Fourier coefficients of a vector is a common task...
The Neural Tangent Kernel (NTK) characterizes the behavior of infinitely...
The Neural Tangent Kernel (NTK) characterizes the behavior of infinitely...
To accelerate kernel methods, we propose a near input sparsity time algo...
Random binning features, introduced in the seminal paper of Rahimi and R...
Kernel methods are fundamental tools in machine learning that allow dete...
The Discrete Fourier Transform (DFT) is a fundamental computational
prim...
Reconstructing continuous signals from a small number of discrete sample...
Many tasks in machine learning and data mining, such as data diversifica...
Random Fourier features is one of the most popular techniques for scalin...