automated machine learning

Deep-n-Cheap: An Automated Search Framework for Low Complexity Deep Learning ACML 2020 Demo Application for the AutoGOAL Framework COLING 2020 Fast, Accurate, and Simple Models for Tabular Data via Augmented Distillation NeurIPS 2020 Iterative Compression of End-to-End ASR Model Using AutoML Interspeech 2020 PyGlove: Symbolic Programming for Automated Machine Learning NeurIPS 2020 Searching to Exploit Memorization Effect in Learning with Noisy Labels ICML 2020 Stepwise Model Selection for Sequence Prediction via Deep Kernel Learning AISTATS 2020 UNAS: Differentiable Architecture Search Meets Reinforcement Learning CVPR 2020 Weighted Sampling for Combined Model Selection and Hyperparameter Tuning AAAI 2020 AM-LFS: AutoML for Loss Function Search ICCV 2019 Approximated Oracle Filter Pruning for Destructive CNN Width Optimization ICML 2019 Automated Machine Learning with Monte-Carlo Tree Search IJCAI 2019 Automatically Learning Data Augmentation Policies for Dialogue Tasks EMNLP 2019 HAQ: Hardware-Aware Automated Quantization With Mixed Precision CVPR 2019 Searching for a Robust Neural Architecture in Four GPU Hours CVPR 2019 Towards Automated Semi-Supervised Learning AAAI 2019 Towards modular and programmable architecture search NeurIPS 2019 Transferable AutoML by Model Sharing Over Grouped Datasets CVPR 2019 Probabilistic Matrix Factorization for Automated Machine Learning NeurIPS 2018 Transfer Learning with Neural AutoML NeurIPS 2018 Auto-WEKA 2.0: Automatic model selection and hyperparameter optimization in WEKA JMLR 2017 Glottal Source Features for Automatic Speech-Based Depression Assessment Interspeech 2017 Learning Feature Engineering for Classification IJCAI 2017 A Brief Review of the ChaLearn AutoML Challenge: Any-time Any-dataset Learning Without Human Intervention AutoML 2016 Towards Automatically-Tuned Neural Networks AutoML 2016