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Editors: Aleksandra Faust, Roman Garnett, Colin White, Frank Hutter, Jacob R. Gardner
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CMA-ES for Post Hoc Ensembling in AutoML: A Great Success and Salvageable Failure
; Proceedings of the Second International Conference on Automated Machine Learning, PMLR 224:1/1-23
Symbolic Explanations for Hyperparameter Optimization
Sarah Segel, Helena Graf, Alexander Tornede, Bernd Bischl, Marius Lindauer; Proceedings of the Second International Conference on Automated Machine Learning, PMLR 224:2/1-22
Poisson Process for Bayesian Optimization
Xiaoxing Wang, Jiaxing Li, Chao Xue, Wei Liu, Weifeng Liu, Xiaokang Yang, Junchi Yan, Dacheng Tao; Proceedings of the Second International Conference on Automated Machine Learning, PMLR 224:3/1-20
Better Practices for Domain Adaptation
Linus Ericsson, Da Li, Timothy Hospedales; Proceedings of the Second International Conference on Automated Machine Learning, PMLR 224:4/1-25
MEOW - Multi-Objective Evolutionary Weapon Detection
Daniel Dimanov, Colin Singleton, Shahin Rostami, Emili Balaguer-Ballester; Proceedings of the Second International Conference on Automated Machine Learning, PMLR 224:5/1-20
Self-Adjusting Weighted Expected Improvement for Bayesian Optimization
Carolin Benjamins, Elena Raponi, Anja Jankovic, Carola Doerr, Marius Lindauer; Proceedings of the Second International Conference on Automated Machine Learning, PMLR 224:6/1-50
MA-BBOB: Many-Affine Combinations of BBOB Functions for Evaluating AutoML Approaches in Noiseless Numerical Black-Box Optimization Contexts
Diederick Vermetten, Furong Ye, Thomas Bäck, Carola Doerr; Proceedings of the Second International Conference on Automated Machine Learning, PMLR 224:7/1-14
Balanced Mixture of Supernets for Learning the CNN Pooling Architecture
Mehraveh Javan Roshtkhari, Matthew Toews, Marco Pedersoli; Proceedings of the Second International Conference on Automated Machine Learning, PMLR 224:8/1-23
AutoGluon–TimeSeries: AutoML for Probabilistic Time Series Forecasting
Oleksandr Shchur, Ali Caner Turkmen, Nick Erickson, Huibin Shen, Alexander Shirkov, Tony Hu, Bernie Wang; Proceedings of the Second International Conference on Automated Machine Learning, PMLR 224:9/1-21
Q(D)O-ES: Population-based Quality (Diversity) Optimisation for Post Hoc Ensemble Selection in AutoML
Lennart Oswald Purucker, Lennart Schneider, Marie Anastacio, Joeran Beel, Bernd Bischl, Holger Hoos; Proceedings of the Second International Conference on Automated Machine Learning, PMLR 224:10/1-34
PS-AAS: Portfolio Selection for Automated Algorithm Selection in Black-Box Optimization
Ana Kostovska, Gjorgjina Cenikj, Diederick Vermetten, Anja Jankovic, Ana Nikolikj, Urban Skvorc, Peter Korosec, Carola Doerr, Tome Eftimov; Proceedings of the Second International Conference on Automated Machine Learning, PMLR 224:11/1-17
Optimal Resource Allocation for Early Stopping-based Neural Architecture Search Methods
Marcel Aach, Eray Inanc, Rakesh Sarma, Morris Riedel, Andreas Lintermann; Proceedings of the Second International Conference on Automated Machine Learning, PMLR 224:12/1-17
AutoRL Hyperparameter Landscapes
Aditya Mohan, Carolin Benjamins, Konrad Wienecke, Alexander Dockhorn, Marius Lindauer; Proceedings of the Second International Conference on Automated Machine Learning, PMLR 224:13/1-27
“No Free Lunch” in Neural Architectures? A Joint Analysis of Expressivity, Convergence, and Generalization
Wuyang Chen, Wei Huang, Zhangyang Wang; Proceedings of the Second International Conference on Automated Machine Learning, PMLR 224:14/1-29
Computationally Efficient High-Dimensional Bayesian Optimization via Variable Selection
Yihang Shen, Carl Kingsford; Proceedings of the Second International Conference on Automated Machine Learning, PMLR 224:15/1-27
Learning Activation Functions for Sparse Neural Networks
Mohammad Loni, Aditya Mohan, Mehdi Asadi, Marius Lindauer; Proceedings of the Second International Conference on Automated Machine Learning, PMLR 224:16/1-19
Searching for Fairer Machine Learning Ensembles
Michael Feffer, Martin Hirzel, Samuel C Hoffman, Kiran Kate, Parikshit Ram, Avraham Shinnar; Proceedings of the Second International Conference on Automated Machine Learning, PMLR 224:17/1-19
Exploiting Network Compressibility and Topology in Zero-Cost NAS
Lichuan Xiang, Rosco Hunter, Minghao Xu, Łukasz Dudziak, Hongkai Wen; Proceedings of the Second International Conference on Automated Machine Learning, PMLR 224:18/1-14
ABLATOR: Robust Horizontal-Scaling of Machine Learning Ablation Experiments
Iordanis Fostiropoulos, Laurent Itti; Proceedings of the Second International Conference on Automated Machine Learning, PMLR 224:19/1-15
Neural Architecture Search for Visual Anomaly Segmentation
Tommie Kerssies, Joaquin Vanschoren; Proceedings of the Second International Conference on Automated Machine Learning, PMLR 224:20/1-14
Cost-Effective Hyperparameter Optimization for Large Language Model Generation Inference
Chi Wang, Xueqing Liu, Ahmed Hassan Awadallah; Proceedings of the Second International Conference on Automated Machine Learning, PMLR 224:21/1-17
AlphaD3M: An Open-Source AutoML Library for Multiple ML Tasks
Roque Lopez, Raoni Lourenco, Remi Rampin, Sonia Castelo, Aécio S. R. Santos, Jorge Henrique Piazentin Ono, Claudio Silva, Juliana Freire; Proceedings of the Second International Conference on Automated Machine Learning, PMLR 224:22/1-22
Multi-Predict: Few Shot Predictors For Efficient Neural Architecture Search
Yash Akhauri, Mohamed S Abdelfattah; Proceedings of the Second International Conference on Automated Machine Learning, PMLR 224:23/1-23
Meta-Learning for Fast Model Recommendation in Unsupervised Multivariate Time Series Anomaly Detection
Jose Manuel Navarro, Alexis Huet, Dario Rossi; Proceedings of the Second International Conference on Automated Machine Learning, PMLR 224:24/1-19
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