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11/12/2021
A Simple and Fast Baseline for Tuning Large XGBoost Models
XGBoost, a scalable tree boosting algorithm, has proven effective for ma...
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06/10/2021
A Nonmyopic Approach to Cost-Constrained Bayesian Optimization
Bayesian optimization (BO) is a popular method for optimizing expensive-...
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06/10/2021
A multi-objective perspective on jointly tuning hardware and hyperparameters
In addition to the best model architecture and hyperparameters, a full A...
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04/16/2021
Overfitting in Bayesian Optimization: an empirical study and early-stopping solution
Bayesian Optimization (BO) is a successful methodology to tune the hyper...
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01/22/2021
Lexical semantic change for Ancient Greek and Latin
Change and its precondition, variation, are inherent in languages. Over ...
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12/15/2020
Amazon SageMaker Automatic Model Tuning: Scalable Black-box Optimization
Tuning complex machine learning systems is challenging. Machine learning...
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12/15/2020
Amazon SageMaker Autopilot: a white box AutoML solution at scale
AutoML systems provide a black-box solution to machine learning problems...
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11/23/2020
Pareto-efficient Acquisition Functions for Cost-Aware Bayesian Optimization
Bayesian optimization (BO) is a popular method to optimize expensive bla...
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06/09/2020
Fair Bayesian Optimization
Given the increasing importance of machine learning (ML) in our lives, a...
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03/22/2020
Cost-aware Bayesian Optimization
Bayesian optimization (BO) is a class of global optimization algorithms,...
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10/15/2019
Constrained Bayesian Optimization with Max-Value Entropy Search
Bayesian optimization (BO) is a model-based approach to sequentially opt...
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09/30/2019
A Copula approach for hyperparameter transfer learning
Bayesian optimization (BO) is a popular methodology to tune the hyperpar...
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09/27/2019
Learning search spaces for Bayesian optimization: Another view of hyperparameter transfer learning
Bayesian optimization (BO) is a successful methodology to optimize black...
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03/13/2019
GASC: Genre-Aware Semantic Change for Ancient Greek
Word meaning changes over time, depending on linguistic and extra-lingui...
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02/16/2018
A Likelihood-Free Inference Framework for Population Genetic Data using Exchangeable Neural Networks
Inference for population genetics models is hindered by computationally ...
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12/08/2017
Multiple Adaptive Bayesian Linear Regression for Scalable Bayesian Optimization with Warm Start
Bayesian optimization (BO) is a model-based approach for gradient-free b...
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09/14/2016
