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Volume 228: International Conference on Automated Machine Learning, 12-15 November 2023, Hasso Plattner Institute, Potsdam, Germany

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Editors: Aleksandra Faust, Roman Garnett, Colin White, Frank Hutter, Jacob R. Gardner

[bib][citeproc]

CMA-ES for Post Hoc Ensembling in AutoML: A Great Success and Salvageable Failure

Lennart Oswald Purucker, Joeran Beel; Proceedings of the Second International Conference on Automated Machine Learning, PMLR 228:1/1-23

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 228:2/1-22

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 228:3/1-20

Better Practices for Domain Adaptation

Linus Ericsson, Da Li, Timothy Hospedales; Proceedings of the Second International Conference on Automated Machine Learning, PMLR 228:4/1-25

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 228:5/1-20

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 228:6/1-50

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 228:7/1-14

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 228:8/1-23

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 228:9/1-21

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 228:10/1-34

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 228:11/1-17

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 228:12/1-17

AutoRL Hyperparameter Landscapes

Aditya Mohan, Carolin Benjamins, Konrad Wienecke, Alexander Dockhorn, Marius Lindauer; Proceedings of the Second International Conference on Automated Machine Learning, PMLR 228:13/1-27

“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 228:14/1-29

Computationally Efficient High-Dimensional Bayesian Optimization via Variable Selection

Yihang Shen, Carl Kingsford; Proceedings of the Second International Conference on Automated Machine Learning, PMLR 228:15/1-27

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 228:16/1-19

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 228:17/1-19

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 228:18/1-14

ABLATOR: Robust Horizontal-Scaling of Machine Learning Ablation Experiments

Iordanis Fostiropoulos, Laurent Itti; Proceedings of the Second International Conference on Automated Machine Learning, PMLR 228:19/1-15

Neural Architecture Search for Visual Anomaly Segmentation

Tommie Kerssies, Joaquin Vanschoren; Proceedings of the Second International Conference on Automated Machine Learning, PMLR 228:20/1-14

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 228:21/1-17

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 228:22/1-22

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 228:23/1-23

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 228:24/1-19

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