AutoML

SPIO: Ensemble and Selective Strategies via LLM-Based Multi-Agent Planning in Automated Data Science ACL 2026 Vision-Oriented Lightweight Neural Architecture Search with Budget-Adaptive Evaluation CVPR 2026 Improving N-Glycosylation and Biopharmaceutical Production Predictions Using AutoML-Built Residual Hybrid Models AISTATS 2025 AutoCD: Automated Machine Learning for Causal Discovery Algorithms PGM 2024 AutoNF: Automated Architecture Optimization of Normalizing Flows with Unconstrained Continuous Relaxation Admitting Optimal Discrete Solution AAAI 2023 AutoTransfer: AutoML with Knowledge Transfer - An Application to Graph Neural Networks ICLR 2023 Learning meta-features for AutoML ICLR 2022 Stock Price Volatility Prediction: A Case Study with AutoML EMNLP 2022 Auto-KWS 2021 Challenge: Task, Datasets, and Baselines Interspeech 2021 Deep-n-Cheap: An Automated Search Framework for Low Complexity Deep Learning ACML 2020 Loss Function Search for Face Recognition ICML 2020 PointAugment: An Auto-Augmentation Framework for Point Cloud Classification CVPR 2020 Run2Survive: A Decision-theoretic Approach to Algorithm Selection based on Survival Analysis ACML 2020 Fast AutoAugment NeurIPS 2019 Auto-WEKA 2.0: Automatic model selection and hyperparameter optimization in WEKA JMLR 2017 Efficient and Robust Automated Machine Learning NeurIPS 2015