SOTAVerified

AutoML

Automated Machine Learning (AutoML) is a general concept which covers diverse techniques for automated model learning including automatic data preprocessing, architecture search, and model selection. Source: Evaluating recommender systems for AI-driven data science (1905.09205)

Source: CHOPT : Automated Hyperparameter Optimization Framework for Cloud-Based Machine Learning Platforms

Papers

Showing 131140 of 641 papers

TitleStatusHype
GAMA: a General Automated Machine learning AssistantCode1
Automating Outlier Detection via Meta-LearningCode1
FLAML: A Fast and Lightweight AutoML LibraryCode1
Extensible Proxy for Efficient NASCode1
AutoML for Climate Change: A Call to ActionCode1
Fast Optimizer BenchmarkCode1
DC-BENCH: Dataset Condensation BenchmarkCode1
AutoML Segmentation for 3D Medical Image Data: Contribution to the MSD Challenge 2018Code1
Evolutionary Neural AutoML for Deep LearningCode1
HPOBench: A Collection of Reproducible Multi-Fidelity Benchmark Problems for HPOCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1marc.boulleRank (AutoML5)6.4Unverified
2reference_mbRank (AutoML5)5.2Unverified
3postech.mlg_exbrainRank (AutoML5)5.2Unverified
4abhishek4Rank (AutoML5)4.6Unverified
5referenceRank (AutoML5)4.4Unverified
6reference_lsRank (AutoML5)4Unverified
7djajeticRank (AutoML5)3Unverified
8aad_freiburgRank (AutoML5)1.6Unverified
#ModelMetricClaimedVerifiedStatus
1Logistic RegressionAccuracy97.02Unverified
#ModelMetricClaimedVerifiedStatus
1Zero-shot-BERT-SORT1:1 Accuracy55Unverified
#ModelMetricClaimedVerifiedStatus
1Logistic Regressionaccuracy98.33Unverified