Aaron Klein
16 papers · 2015–2025 · 5 venues · across top CS/AI venues
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Achievements
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🗺️ Taxonomy Completionist (27) 🏃 Academic Marathon · Half 🌍 Conference Polyglot · Silver 🌉 Interdisciplinary Bridge · Silver 🐣 Hot Topic Early Bird
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Topic Pioneer
🧭
Keyword Pioneer
📈
Trend Setter
🔥
Unstoppable · Bronze
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Conference Pioneer
💎
Century Club · Bronze
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Keyword Collector
(62)
Top co-authors
Research topics
Machine Learning
(15)
Optimization & Theory
(13)
Artificial Intelligence
(9)
Application Areas
(5)
Learning Paradigms
(5)
Bayesian & Probabilistic · Machine Learning
(3)
Core AI
(3)
Core Methods
(3)
Learning Types · Machine Learning
(3)
Deep Learning
(2)
Natural Language Processing
(2)
Bayesian & Probabilistic · Artificial Intelligence
(2)
Resources & Methods
(2)
Mathematics & Optimization
(1)
Learning Types · Deep Learning
(1)
Keywords
hyperparameter optimization
(9)
bayesian optimization
(8)
surrogate model
(4)
transfer learning
(3)
model selection
(3)
neural architecture search
(2)
ensemble learning
(2)
multi-objective optimization
(2)
multi-task learning
(2)
gaussian process
(2)
automated machine learning
(2)
conformal prediction
(1)
distributed learning
(1)
neural network optimization
(1)
embedding
(1)
sample efficiency
(1)
density ratio estimation
(1)
neural network training
(1)
quantile regression
(1)
automatic relevance determination
(1)
Papers
Hyperband-based Bayesian Optimization for Black-box Prompt Selection
ICML 2025
Obeying the Order: Introducing Ordered Transfer Hyperparameter Optimization
AutoML 2025
HW-GPT-Bench: Hardware-Aware Architecture Benchmark for Language Models
NeurIPS 2024
Optimizing Hyperparameters with Conformal Quantile Regression
ICML 2023
Automatic Termination for Hyperparameter Optimization
AutoML 2022
Syne Tune: A Library for Large Scale Hyperparameter Tuning and Reproducible Research
AutoML 2022
BORE: Bayesian Optimization by Density-Ratio Estimation
ICML 2021
Hyperparameter Transfer Learning with Adaptive Complexity
AISTATS 2021
Meta-Surrogate Benchmarking for Hyperparameter Optimization
NeurIPS 2019
NAS-Bench-101: Towards Reproducible Neural Architecture Search
ICML 2019
BOHB: Robust and Efficient Hyperparameter Optimization at Scale
ICML 2018
Uncertainty Estimates and Multi-Hypotheses Networks for Optical Flow
ECCV 2018
Fast Bayesian Optimization of Machine Learning Hyperparameters on Large Datasets
AISTATS 2017
Bayesian Optimization with Robust Bayesian Neural Networks
NeurIPS 2016
Towards Automatically-Tuned Neural Networks
AutoML 2016
Efficient and Robust Automated Machine Learning
NeurIPS 2015