Search Results for author: Zack Nado

Found 2 papers, 1 papers with code

A Simple Approach to Improve Single-Model Deep Uncertainty via Distance-Awareness

2 code implementations1 May 2022 Jeremiah Zhe Liu, Shreyas Padhy, Jie Ren, Zi Lin, Yeming Wen, Ghassen Jerfel, Zack Nado, Jasper Snoek, Dustin Tran, Balaji Lakshminarayanan

The most popular approaches to estimate predictive uncertainty in deep learning are methods that combine predictions from multiple neural networks, such as Bayesian neural networks (BNNs) and deep ensembles.

Data Augmentation Probabilistic Deep Learning +1

Predicting the utility of search spaces for black-box optimization:a simple, budget-aware approach

no code implementations15 Dec 2021 Setareh Ariafar, Justin Gilmer, Zack Nado, Jasper Snoek, Rodolphe Jenatton, George E. Dahl

For example, when tuning hyperparameters for machine learning pipelines on a new problem given a limited budget, one must strike a balance between excluding potentially promising regions and keeping the search space small enough to be tractable.

Bayesian Optimization

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