Search Results for author:
Found 3 papers, 2 papers with code
Sample Efficient Learning of Predictors that Complement Humans
One of the goals of learning algorithms is to complement and reduce the burden on human decision makers.
Hermite Polynomial Features for Private Data Generation
Hence, a relatively low order of Hermite polynomial features can more accurately approximate the mean embedding of the data distribution compared to a significantly higher number of random features.
Compressibility Measures for Affinely Singular Random Vectors
When considering discrete-domain moving-average processes with non-Gaussian excitation noise, the above results allow us to evaluate the block-average RID and DRB, as well as to determine a relationship between these parameters and other existing compressibility measures.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
