Bayesian Optimization

method ID: bayesianoptimization

Related Papers

Efficient Hyper-parameter Optimization for NLP Applications

Authors: nan

Publication: TIPSTER (2015)

DOI: nan

Hyper-parameter optimization is an im- portant problem in natural language pro- cessing (NLP) and machine learning. Re- cently, a group of studies has focused on using sequential Bayesian Optimization to …...

34318

Learning the Curriculum with Bayesian Optimization for Task-Specific Word Representation Learning

Authors: nan

Publication: TIPSTER (2016)

DOI: nan

We use Bayesian optimization to learn curricula for word representation learning, optimizing performance on downstream tasks that depend on the learned represen- tations as features. The curricula are mod- eled …...

40606

Speed-Constrained Tuning for Statistical Machine Translation Using Bayesian Optimization

Authors: nan

Publication: TIPSTER (2016)

DOI: nan

We address the problem of automatically finding the parameters of a statistical ma- chine translation system that maximize BLEU scores while ensuring that decoding speed ex- ceeds a minimum value. …...

23257

Learning to select data for transfer learning with Bayesian Optimization

Authors: nan

Publication: TIPSTER (2017)

DOI: nan

AbstractDomain similarity measures can be used to gauge adaptability and select suitable data for transfer learning, but existing approaches define ad hoc measures that are deemed suitable for respective tasks. …...

33082

Interactive Text Ranking with Bayesian Optimization: A Case Study on Community QA and Summarization

Authors: nan

Publication: TIPSTER (2020)

DOI: nan

AbstractFor many NLP applications, such as question answering and summarization, the goal is to select the best solution from a large space of candidates to meet a particular user’s needs. …...

26907

Text AutoAugment: Learning Compositional Augmentation Policy for Text Classification

Authors: nan

Publication: TIPSTER (2021)

DOI: nan

AbstractData augmentation aims to enrich training samples for alleviating the overfitting issue in low-resource or class-imbalanced situations. Traditional methods first devise task-specific operations such as Synonym Substitute, then preset the …...

30993