Search Results for author:
Found 5 papers, 3 papers with code
Open Source Vizier: Distributed Infrastructure and API for Reliable and Flexible Blackbox Optimization
Vizier is the de-facto blackbox and hyperparameter optimization service across Google, having optimized some of Google's largest products and research efforts.
Towards Learning Universal Hyperparameter Optimizers with Transformers
Meta-learning hyperparameter optimization (HPO) algorithms from prior experiments is a promising approach to improve optimization efficiency over objective functions from a similar distribution.
OmniPred: Language Models as Universal Regressors
Over the broad landscape of experimental design, regression has been a powerful tool to accurately predict the outcome metrics of a system or model given a set of parameters, but has been traditionally restricted to methods which are only applicable to a specific task.
A Generalized Framework for Population Based Training
Population Based Training (PBT) is a recent approach that jointly optimizes neural network weights and hyperparameters which periodically copies weights of the best performers and mutates hyperparameters during training.
Neural Architecture Search for Energy Efficient Always-on Audio Models
Mobile and edge computing devices for always-on classification tasks require energy-efficient neural network architectures.
