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Volume 224: 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
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
; Proceedings of the Second International Conference on Automated Machine Learning, PMLR 224:2/1-22
Poisson Process for Bayesian Optimization
; Proceedings of the Second International Conference on Automated Machine Learning, PMLR 224:3/1-20
Better Practices for Domain Adaptation
; Proceedings of the Second International Conference on Automated Machine Learning, PMLR 224:4/1-25
MEOW - Multi-Objective Evolutionary Weapon Detection
; Proceedings of the Second International Conference on Automated Machine Learning, PMLR 224:5/1-20
Self-Adjusting Weighted Expected Improvement for Bayesian Optimization
; 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
; 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
; Proceedings of the Second International Conference on Automated Machine Learning, PMLR 224:8/1-23
AutoGluon–TimeSeries: AutoML for Probabilistic Time Series Forecasting
; 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
; 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
; 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
; Proceedings of the Second International Conference on Automated Machine Learning, PMLR 224:12/1-17
AutoRL Hyperparameter Landscapes
; 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
; Proceedings of the Second International Conference on Automated Machine Learning, PMLR 224:14/1-29
Computationally Efficient High-Dimensional Bayesian Optimization via Variable Selection
; Proceedings of the Second International Conference on Automated Machine Learning, PMLR 224:15/1-27
Learning Activation Functions for Sparse Neural Networks
; Proceedings of the Second International Conference on Automated Machine Learning, PMLR 224:16/1-19
Searching for Fairer Machine Learning Ensembles
; Proceedings of the Second International Conference on Automated Machine Learning, PMLR 224:17/1-19
Exploiting Network Compressibility and Topology in Zero-Cost NAS
; Proceedings of the Second International Conference on Automated Machine Learning, PMLR 224:18/1-14
ABLATOR: Robust Horizontal-Scaling of Machine Learning Ablation Experiments
; Proceedings of the Second International Conference on Automated Machine Learning, PMLR 224:19/1-15
Neural Architecture Search for Visual Anomaly Segmentation
; 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
; 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
; 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
; 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
; Proceedings of the Second International Conference on Automated Machine Learning, PMLR 224:24/1-19
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