Guidelines for the Quality Assessment of Energy-Aware NAS Benchmarks
Fuente:
arXiv
Saved in:
| Main Authors: | Kocher, Nick, Wassermann, Christian, Hennig, Leona, Seng, Jonas, Hoos, Holger, Kersting, Kristian, Lindauer, Marius, Müller, Matthias |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Towards Leveraging AutoML for Sustainable Deep Learning: A Multi-Objective HPO Approach on Deep Shift Neural Networks
by: Hennig, Leona, et al.
Published: (2024)
by: Hennig, Leona, et al.
Published: (2024)
Dynamic Priors in Bayesian Optimization for Hyperparameter Optimization
by: Fehring, Lukas, et al.
Published: (2025)
by: Fehring, Lukas, et al.
Published: (2025)
Hyperparameter Optimization via Interacting with Probabilistic Circuits
by: Seng, Jonas, et al.
Published: (2025)
by: Seng, Jonas, et al.
Published: (2025)
ARLBench: Flexible and Efficient Benchmarking for Hyperparameter Optimization in Reinforcement Learning
by: Becktepe, Jannis, et al.
Published: (2024)
by: Becktepe, Jannis, et al.
Published: (2024)
Optimizing Time Series Forecasting Architectures: A Hierarchical Neural Architecture Search Approach
by: Deng, Difan, et al.
Published: (2024)
by: Deng, Difan, et al.
Published: (2024)
carps: A Framework for Comparing N Hyperparameter Optimizers on M Benchmarks
by: Benjamins, Carolin, et al.
Published: (2025)
by: Benjamins, Carolin, et al.
Published: (2025)
Scaling Probabilistic Circuits via Data Partitioning
by: Seng, Jonas, et al.
Published: (2025)
by: Seng, Jonas, et al.
Published: (2025)
Growing with Experience: Growing Neural Networks in Deep Reinforcement Learning
by: Fehring, Lukas, et al.
Published: (2025)
by: Fehring, Lukas, et al.
Published: (2025)
Revisiting Learning Rate Control
by: Henheik, Micha, et al.
Published: (2025)
by: Henheik, Micha, et al.
Published: (2025)
Dynamic Hyperparameter Importance for Efficient Multi-Objective Optimization
by: Theodorakopoulos, Daphne, et al.
Published: (2026)
by: Theodorakopoulos, Daphne, et al.
Published: (2026)
EC-NAS: Energy Consumption Aware Tabular Benchmarks for Neural Architecture Search
by: Bakhtiarifard, Pedram, et al.
Published: (2022)
by: Bakhtiarifard, Pedram, et al.
Published: (2022)
Systems with Switching Causal Relations: A Meta-Causal Perspective
by: Willig, Moritz, et al.
Published: (2024)
by: Willig, Moritz, et al.
Published: (2024)
Auto-nnU-Net: Towards Automated Medical Image Segmentation
by: Becktepe, Jannis, et al.
Published: (2025)
by: Becktepe, Jannis, et al.
Published: (2025)
On the Efficiency of Training Robust Decision Trees
by: Gerlach, Benedict, et al.
Published: (2025)
by: Gerlach, Benedict, et al.
Published: (2025)
When Are RL Hyperparameters Benign? A Study in Offline Goal-Conditioned RL
by: Töpperwien, Jan Malte, et al.
Published: (2026)
by: Töpperwien, Jan Malte, et al.
Published: (2026)
All Eyes on the Workflow: Automated and Efficient Event Discovery from Video Streams
by: Pegoraro, Marco, et al.
Published: (2026)
by: Pegoraro, Marco, et al.
Published: (2026)
Hyperparameter Importance Analysis for Multi-Objective AutoML
by: Theodorakopoulos, Daphne, et al.
Published: (2024)
by: Theodorakopoulos, Daphne, et al.
Published: (2024)
Moments Matter:Stabilizing Policy Optimization using Return Distributions
by: Jabs, Dennis, et al.
Published: (2026)
by: Jabs, Dennis, et al.
Published: (2026)
Structure in Deep Reinforcement Learning: A Survey and Open Problems
by: Mohan, Aditya, et al.
Published: (2023)
by: Mohan, Aditya, et al.
Published: (2023)
auto-sktime: Automated Time Series Forecasting
by: Zöller, Marc-André, et al.
Published: (2023)
by: Zöller, Marc-André, et al.
Published: (2023)
HyperSHAP: Shapley Values and Interactions for Explaining Hyperparameter Optimization
by: Wever, Marcel, et al.
Published: (2025)
by: Wever, Marcel, et al.
Published: (2025)
Interactive Hyperparameter Optimization in Multi-Objective Problems via Preference Learning
by: Giovanelli, Joseph, et al.
Published: (2023)
by: Giovanelli, Joseph, et al.
Published: (2023)
Deep Classifier Mimicry without Data Access
by: Braun, Steven, et al.
Published: (2023)
by: Braun, Steven, et al.
Published: (2023)
OCALM: Object-Centric Assessment with Language Models
by: Kaufmann, Timo, et al.
Published: (2024)
by: Kaufmann, Timo, et al.
Published: (2024)
SocialGrid: A Benchmark for Planning and Social Reasoning in Embodied Multi-Agent Systems
by: Shindo, Hikaru, et al.
Published: (2026)
by: Shindo, Hikaru, et al.
Published: (2026)
Credibility-Aware Multi-Modal Fusion Using Probabilistic Circuits
by: Sidheekh, Sahil, et al.
Published: (2024)
by: Sidheekh, Sahil, et al.
Published: (2024)
Combining Automated Optimisation of Hyperparameters and Reward Shape
by: Dierkes, Julian, et al.
Published: (2024)
by: Dierkes, Julian, et al.
Published: (2024)
Neural Attention Search Linear: Towards Adaptive Token-Level Hybrid Attention Models
by: Deng, Difan, et al.
Published: (2026)
by: Deng, Difan, et al.
Published: (2026)
Rethinking Evaluation Paradigms in IBP-based Certified Training
by: Kaulen, Konstantin, et al.
Published: (2026)
by: Kaulen, Konstantin, et al.
Published: (2026)
Depth-Recurrent Attention Mixtures: Giving Latent Reasoning the Attention it Deserves
by: Knupp, Jonas, et al.
Published: (2026)
by: Knupp, Jonas, et al.
Published: (2026)
AutoML for Multi-Class Anomaly Compensation of Sensor Drift
by: Schaller, Melanie, et al.
Published: (2025)
by: Schaller, Melanie, et al.
Published: (2025)
Gradient-Informed Bayesian and Interior Point Optimization for Efficient Inverse Design in Nanophotonics
by: Mahlau, Yannik, et al.
Published: (2026)
by: Mahlau, Yannik, et al.
Published: (2026)
GRAIL: Autonomous Concept Grounding for Neuro-Symbolic Reinforcement Learning
by: Shindo, Hikaru, et al.
Published: (2026)
by: Shindo, Hikaru, et al.
Published: (2026)
Polynomial Regret Concentration of UCB for Non-Deterministic State Transitions
by: Cömer, Can, et al.
Published: (2025)
by: Cömer, Can, et al.
Published: (2025)
HackAtari: Atari Learning Environments for Robust and Continual Reinforcement Learning
by: Delfosse, Quentin, et al.
Published: (2024)
by: Delfosse, Quentin, et al.
Published: (2024)
Object Centric Concept Bottlenecks
by: Steinmann, David, et al.
Published: (2025)
by: Steinmann, David, et al.
Published: (2025)
Learning to Intervene on Concept Bottlenecks
by: Steinmann, David, et al.
Published: (2023)
by: Steinmann, David, et al.
Published: (2023)
Be Careful What You Smooth For: Label Smoothing Can Be a Privacy Shield but Also a Catalyst for Model Inversion Attacks
by: Struppek, Lukas, et al.
Published: (2023)
by: Struppek, Lukas, et al.
Published: (2023)
Instance Selection for Dynamic Algorithm Configuration with Reinforcement Learning: Improving Generalization
by: Benjamins, Carolin, et al.
Published: (2024)
by: Benjamins, Carolin, et al.
Published: (2024)
Checkmating One, by Using Many: Combining Mixture of Experts with MCTS to Improve in Chess
by: Helfenstein, Felix, et al.
Published: (2024)
by: Helfenstein, Felix, et al.
Published: (2024)
Similar Items
-
Towards Leveraging AutoML for Sustainable Deep Learning: A Multi-Objective HPO Approach on Deep Shift Neural Networks
by: Hennig, Leona, et al.
Published: (2024) -
Dynamic Priors in Bayesian Optimization for Hyperparameter Optimization
by: Fehring, Lukas, et al.
Published: (2025) -
Hyperparameter Optimization via Interacting with Probabilistic Circuits
by: Seng, Jonas, et al.
Published: (2025) -
ARLBench: Flexible and Efficient Benchmarking for Hyperparameter Optimization in Reinforcement Learning
by: Becktepe, Jannis, et al.
Published: (2024) -
Optimizing Time Series Forecasting Architectures: A Hierarchical Neural Architecture Search Approach
by: Deng, Difan, et al.
Published: (2024)