hyperparameter tuning

Bayesian Optimization for Iterative Learning NeurIPS 2020 BINOCULARS for efficient, nonmyopic sequential experimental design ICML 2020 Can Weight Sharing Outperform Random Architecture Search? An Investigation With TuNAS CVPR 2020 Counterfactual Cross-Validation: Stable Model Selection Procedure for Causal Inference Models ICML 2020 Dynamically Adjusting Transformer Batch Size by Monitoring Gradient Direction Change ACL 2020 Efficient Large-Scale Gaussian Process Bandits by Believing only Informative Actions L4DC 2020 Evaluating Word Embeddings on Low-Resource Languages EMNLP 2020 Inefficiency of K-FAC for Large Batch Size Training AAAI 2020 Knowing The What But Not The Where in Bayesian Optimization ICML 2020 KungFu: Making Training in Distributed Machine Learning Adaptive OSDI 2020 Learning to Auto Weight: Entirely Data-Driven and Highly Efficient Weighting Framework AAAI 2020 MFE: Towards reproducible meta-feature extraction JMLR 2020 Mixed-Variable Bayesian Optimization IJCAI 2020 NAS-Bench-1Shot1: Benchmarking and Dissecting One-shot Neural Architecture Search ICLR 2020 On hyperparameter tuning in general clustering problemsm ICML 2020 Optimizer Benchmarking Needs to Account for Hyperparameter Tuning ICML 2020 Rethinking the Hyperparameters for Fine-tuning ICLR 2020 The Cost-free Nature of Optimally Tuning Tikhonov Regularizers and Other Ordered Smoothers ICML 2020 Tuning Causal Discovery Algorithms PGM 2020 Tuning Hyperparameters without Grad Students: Scalable and Robust Bayesian Optimisation with Dragonfly JMLR 2020 Unsupervised Model Selection for Variational Disentangled Representation Learning ICLR 2020 Weighted Sampling for Combined Model Selection and Hyperparameter Tuning AAAI 2020 A Large-Scale Study on Regularization and Normalization in GANs ICML 2019 Asynchronous Batch Bayesian Optimisation with Improved Local Penalisation ICML 2019 Augmenting and Tuning Knowledge Graph Embeddings UAI 2019