{"url":"/dataset/ea-has-bench","name":"EA-HAS-Bench","full_name":"Energy-Aware Hyperparameter and Architecture Search Benchmark","description_markdown":"We present the first large-scale energy-aware benchmark that allows studying AutoML methods to achieve better trade-offs between performance and search energy consumption, named EA-HAS-Bench. EA-HAS-Bench provides a large-scale architecture/hyperparameter joint search space, covering diversified configurations related to energy consumption. Furthermore, we propose a novel surrogate model specially designed for large joint search space, which proposes a Bezier curve-based model to predict learning curves with unlimited shape and length.","description_withheld":null,"homepage":"https://github.com/microsoft/EA-HAS-Bench","introduced_date":"2023-05-01","introduced_date_note":null,"introduced_by":{"paper":"/paper/ea-has-bench-energy-aware-hyperparameter-and","title":"EA-HAS-Bench:Energy-Aware Hyperparameter and Architecture Search Benchmark","first_author":"Shuguang Dou","url":null},"license":{"name":"MIT License      Copyright (c) Microsoft Corporation.      Permission is hereby granted, free of charge, to any person obtaining a copy     of this software and associated documentation files (the \"Software\"), to deal     in the Software without restriction, including without limitation the rights     to use, copy, modify, merge, publish, distribute, sublicense, and/or sell     copies of the Software, and to permit persons to whom the Software is    furnished to do so, subject to the following","url":null},"modalities":[],"tasks":[{"name":"Neural Architecture Search","url":"/task/architecture-search","datasets_with_task":"/datasets/task/architecture-search"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["EA-HAS-Bench"],"data_loaders":[],"num_papers_in_archive":1,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}