54 citations · 79 across the 21 of their papers we have counts for
4 papers · 1 filter
Stable Tensor Neural Networks for Rapid Deep Learning
Elizabeth Newman, Lior Horesh, Haim Avron +1
We propose a tensor neural network (-NN) framework that offers an exciting new paradigm for designing neural networks with multidimensional (tensor) data. Our network architectu…
Random Fourier Features for Kernel Ridge Regression: Approximation Bounds and Statistical Guarantees
Haim Avron, Michael Kapralov, Cameron Musco +3
Random Fourier features is one of the most popular techniques for scaling up kernel methods, such as kernel ridge regression. However, despite impressive empirical results, the sta…
Sketching for Principal Component Regression
Liron Mor-Yosef, Haim Avron
Principal component regression (PCR) is a useful method for regularizing linear regression. Although conceptually simple, straightforward implementations of PCR have high computati…
Stochastic Chebyshev Gradient Descent for Spectral Optimization
Insu Han, Haim Avron, Jinwoo Shin
A large class of machine learning techniques requires the solution of optimization problems involving spectral functions of parametric matrices, e.g. log-determinant and nuclear no…