82 citations · 151 across the 23 of their papers we have counts for
3 papers · 1 filter
A Universal Sampling Method for Reconstructing Signals with Simple Fourier Transforms
Haim Avron, Michael Kapralov, Cameron Musco +3
Reconstructing continuous signals from a small number of discrete samples is a fundamental problem across science and engineering. In practice, we are often interested in signals w…
Beyond -Approximation for Submodular Maximization on Massive Data Streams
Ashkan Norouzi-Fard, Jakub Tarnawski, Slobodan Mitrović +3
Many tasks in machine learning and data mining, such as data diversification, non-parametric learning, kernel machines, clustering etc., require extracting a small but representati…
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…