Aaron Klein - RankMe

51 papers A* 7A 2Journal 28Unranked 11

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Evolutionary Architecture Search through Grammar-Based Sequence Alignment. CoRR Adri Gomez Martin, Felix Möller, Steven McDonagh, Mónica Abella, Manuel Desco, Elliot J. Crowley, Aaron Klein, Linus Ericsson
2025	A*	`conf`	Hyperband-based Bayesian Optimization for Black-box Prompt Selection. ICML Lennart Schneider, Martin Wistuba, Aaron Klein, Jacek Golebiowski, Giovanni Zappella, Felice Antonio Merra
2025	J	`jnl`	Hyperparameter Optimization in Machine Learning. Found. Trends Mach. Learn. Luca Franceschi, Michele Donini, Valerio Perrone, Aaron Klein, Cédric Archambeau, Matthias W. Seeger, Massimiliano Pontil, Paolo Frasconi
2025	J	`jnl`	Improving LLM-based Global Optimization with Search Space Partitioning. CoRR Andrej Schwanke, Lyubomir Ivanov, David Salinas, Fabio Ferreira, Aaron Klein, Frank Hutter, Arber Zela
2025	—	`conf`	Obeying the Order: Introducing Ordered Transfer Hyperparameter Optimization. AutoML Sigrid Passano Hellan, Huibin Shen, Francois-Xavier Aubet, David Salinas, Aaron Klein
2025	J	`jnl`	Where to Begin: Efficient Pretraining via Subnetwork Selection and Distillation. CoRR Arjun Krishnakumar, Rhea Sanjay Sukthanker, Hannan Javed Mahadik, Gabriela Kadlecová, Vladyslav Moroshan, Timur Carstensen, Frank Hutter, Aaron Klein
2024	A*	`conf`	HW-GPT-Bench: Hardware-Aware Architecture Benchmark for Language Models. NeurIPS Rhea Sanjay Sukthanker, Arber Zela, Benedikt Staffler, Aaron Klein, Lennart Purucker, Jörg K. H. Franke, Frank Hutter
2024	J	`jnl`	Hyperband-based Bayesian Optimization for Black-box Prompt Selection. CoRR Lennart Schneider, Martin Wistuba, Aaron Klein, Jacek Golebiowski, Giovanni Zappella, Felice Antonio Merra
2024	J	`jnl`	Hyperparameter Optimization in Machine Learning. CoRR Luca Franceschi, Michele Donini, Valerio Perrone, Aaron Klein, Cédric Archambeau, Matthias W. Seeger, Massimiliano Pontil, Paolo Frasconi
2024	J	`jnl`	LLM Compression with Neural Architecture Search. CoRR Rhea Sanjay Sukthanker, Benedikt Staffler, Frank Hutter, Aaron Klein
2024	J	`jnl`	Structural Pruning of Pre-trained Language Models via Neural Architecture Search. CoRR Aaron Klein, Jacek Golebiowski, Xingchen Ma, Valerio Perrone, Cédric Archambeau
2024	J	`jnl`	Structural Pruning of Pre-trained Language Models via Neural Architecture Search. Trans. Mach. Learn. Res. Aaron Klein, Jacek Golebiowski, Xingchen Ma, Valerio Perrone, Cédric Archambeau
2024	J	`jnl`	Warmstarting for Scaling Language Models. CoRR Neeratyoy Mallik, Maciej Janowski, Johannes Hog, Herilalaina Rakotoarison, Aaron Klein, Josif Grabocka, Frank Hutter
2023	J	`jnl`	Obeying the Order: Introducing Ordered Transfer Hyperparameter Optimisation. CoRR Sigrid Passano Hellan, Huibin Shen, François-Xavier Aubet, David Salinas, Aaron Klein
2023	A*	`conf`	Optimizing Hyperparameters with Conformal Quantile Regression. ICML David Salinas, Jacek Golebiowski, Aaron Klein, Matthias W. Seeger, Cédric Archambeau
2023	J	`jnl`	Optimizing Hyperparameters with Conformal Quantile Regression. CoRR David Salinas, Jacek Golebiowski, Aaron Klein, Matthias W. Seeger, Cédric Archambeau
2023	J	`jnl`	Robust Level-Set-Based Topology Optimization Under Uncertainties Using Anchored ANOVA Petrov-Galerkin Method. SIAM/ASA J. Uncertain. Quantification Christophe Audouze, Aaron Klein, Adrian Butscher, Nigel J. W. Morris, Prasanth Nair, Masayuki Yano
2022	—	`conf`	Automatic Termination for Hyperparameter Optimization. AutoML Anastasia Makarova, Huibin Shen, Valerio Perrone, Aaron Klein, Jean Baptiste Faddoul, Andreas Krause, Matthias W. Seeger, Cédric Archambeau
2022	—	`conf`	Syne Tune: A Library for Large Scale Hyperparameter Tuning and Reproducible Research. AutoML David Salinas, Matthias W. Seeger, Aaron Klein, Valerio Perrone, Martin Wistuba, Cédric Archambeau
2021	A*	`conf`	BORE: Bayesian Optimization by Density-Ratio Estimation. ICML Louis C. Tiao, Aaron Klein, Matthias W. Seeger, Edwin V. Bonilla, Cédric Archambeau, Fabio Ramos
2021	J	`jnl`	BORE: Bayesian Optimization by Density-Ratio Estimation. CoRR Louis C. Tiao, Aaron Klein, Matthias W. Seeger, Edwin V. Bonilla, Cédric Archambeau, Fabio Ramos
2021	—	`conf`	HPOBench: A Collection of Reproducible Multi-Fidelity Benchmark Problems for HPO. NeurIPS Datasets and Benchmarks Katharina Eggensperger, Philipp Müller, Neeratyoy Mallik, Matthias Feurer, René Sass, Aaron Klein, Noor H. Awad, Marius Lindauer, Frank Hutter
2021	J	`jnl`	HPOBench: A Collection of Reproducible Multi-Fidelity Benchmark Problems for HPO. CoRR Katharina Eggensperger, Philipp Müller, Neeratyoy Mallik, Matthias Feurer, René Sass, Aaron Klein, Noor H. Awad, Marius Lindauer, Frank Hutter
2021	A	`conf`	Hyperparameter Transfer Learning with Adaptive Complexity. AISTATS Samuel Horváth, Aaron Klein, Peter Richtárik, Cédric Archambeau
2021	J	`jnl`	Hyperparameter Transfer Learning with Adaptive Complexity. CoRR Samuel Horváth, Aaron Klein, Peter Richtárik, Cédric Archambeau
2021	J	`jnl`	Online Optimization of Stimulation Speed in an Auditory Brain-Computer Interface under Time Constraints. CoRR Jan Sosulski, David Hübner, Aaron Klein, Michael Tangermann
2021	J	`jnl`	Overfitting in Bayesian Optimization: an empirical study and early-stopping solution. CoRR Anastasia Makarova, Huibin Shen, Valerio Perrone, Aaron Klein, Jean Baptiste Faddoul, Andreas Krause, Matthias W. Seeger, Cédric Archambeau
2020	—	`—`	Efficient bayesian hyperparameter optimization Aaron Klein
2020	J	`jnl`	Model-based Asynchronous Hyperparameter Optimization. CoRR Louis C. Tiao, Aaron Klein, Cédric Archambeau, Matthias W. Seeger
2019	—	`ch.`	Auto-sklearn: Efficient and Robust Automated Machine Learning. Automated Machine Learning Matthias Feurer, Aaron Klein, Katharina Eggensperger, Jost Tobias Springenberg, Manuel Blum, Frank Hutter
2019	A*	`conf`	Meta-Surrogate Benchmarking for Hyperparameter Optimization. NeurIPS Aaron Klein, Zhenwen Dai, Frank Hutter, Neil D. Lawrence, Javier González
2019	J	`jnl`	Meta-Surrogate Benchmarking for Hyperparameter Optimization. CoRR Aaron Klein, Zhenwen Dai, Frank Hutter, Neil D. Lawrence, Javier González
2019	A*	`conf`	NAS-Bench-101: Towards Reproducible Neural Architecture Search. ICML Chris Ying, Aaron Klein, Eric Christiansen, Esteban Real, Kevin Murphy, Frank Hutter
2019	J	`jnl`	NAS-Bench-101: Towards Reproducible Neural Architecture Search. CoRR Chris Ying, Aaron Klein, Esteban Real, Eric Christiansen, Kevin Murphy, Frank Hutter
2019	J	`jnl`	Probabilistic Rollouts for Learning Curve Extrapolation Across Hyperparameter Settings. CoRR Matilde Gargiani, Aaron Klein, Stefan Falkner, Frank Hutter
2019	J	`jnl`	Tabular Benchmarks for Joint Architecture and Hyperparameter Optimization. CoRR Aaron Klein, Frank Hutter
2019	—	`ch.`	Towards Automatically-Tuned Deep Neural Networks. Automated Machine Learning Hector Mendoza, Aaron Klein, Matthias Feurer, Jost Tobias Springenberg, Matthias Urban, Michael Burkart, Maximilian Dippel, Marius Lindauer, Frank Hutter
2018	A*	`conf`	BOHB: Robust and Efficient Hyperparameter Optimization at Scale. ICML Stefan Falkner, Aaron Klein, Frank Hutter
2018	J	`jnl`	BOHB: Robust and Efficient Hyperparameter Optimization at Scale. CoRR Stefan Falkner, Aaron Klein, Frank Hutter
2018	—	`conf`	Practical Hyperparameter Optimization for Deep Learning. ICLR (Workshop) Stefan Falkner, Aaron Klein, Frank Hutter
2018	J	`jnl`	Towards Automated Deep Learning: Efficient Joint Neural Architecture and Hyperparameter Search. CoRR Arber Zela, Aaron Klein, Stefan Falkner, Frank Hutter
2018	—	`conf`	Uncertainty Estimates and Multi-hypotheses Networks for Optical Flow. ECCV (7) Eddy Ilg, Özgün Çiçek, Silvio Galesso, Aaron Klein, Osama Makansi, Frank Hutter, Thomas Brox
2018	J	`jnl`	Uncertainty Estimates for Optical Flow with Multi-Hypotheses Networks. CoRR Eddy Ilg, Özgün Çiçek, Silvio Galesso, Aaron Klein, Osama Makansi, Frank Hutter, Thomas Brox
2017	A	`conf`	Fast Bayesian Optimization of Machine Learning Hyperparameters on Large Datasets. AISTATS Aaron Klein, Stefan Falkner, Simon Bartels, Philipp Hennig, Frank Hutter
2017	—	`conf`	Learning Curve Prediction with Bayesian Neural Networks. ICLR (Poster) Aaron Klein, Stefan Falkner, Jost Tobias Springenberg, Frank Hutter
2017	—	`conf`	The Sacred Infrastructure for Computational Research. SciPy Klaus Greff, Aaron Klein, Martin Chovanec, Frank Hutter, Jürgen Schmidhuber
2016	J	`jnl`	Asynchronous Stochastic Gradient MCMC with Elastic Coupling. CoRR Jost Tobias Springenberg, Aaron Klein, Stefan Falkner, Frank Hutter
2016	—	`conf`	Bayesian Optimization with Robust Bayesian Neural Networks. NIPS Jost Tobias Springenberg, Aaron Klein, Stefan Falkner, Frank Hutter
2016	J	`jnl`	Fast Bayesian Optimization of Machine Learning Hyperparameters on Large Datasets. CoRR Aaron Klein, Stefan Falkner, Simon Bartels, Philipp Hennig, Frank Hutter
2016	—	`conf`	Towards Automatically-Tuned Neural Networks. AutoML@ICML Hector Mendoza, Aaron Klein, Matthias Feurer, Jost Tobias Springenberg, Frank Hutter
2015	—	`conf`	Efficient and Robust Automated Machine Learning. NIPS Matthias Feurer, Aaron Klein, Katharina Eggensperger, Jost Tobias Springenberg, Manuel Blum, Frank Hutter