no code implementations • 28 Feb 2022 • Francesco Quinzan, Rajiv Khanna, Moshik Hershcovitch, Sarel Cohen, Daniel G. Waddington, Tobias Friedrich, Michael W. Mahoney
We study the fundamental problem of selecting optimal features for model construction.
no code implementations • 21 Feb 2022 • Andrew Wood, Moshik Hershcovitch, Daniel Waddington, Sarel Cohen, Peter Chin
Bayesian inference allows machine learning models to express uncertainty.
no code implementations • 21 Feb 2022 • Andrew Wood, Moshik Hershcovitch, Daniel Waddington, Sarel Cohen, Meredith Wolf, Hongjun Suh, Weiyu Zong, Peter Chin
Dimensionality reduction algorithms are frequently used to augment downstream tasks such as machine learning, data science, and also are exploratory methods for understanding complex phenomena.