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 6170 of 641 papers

TitleStatusHype
Fast Optimizer BenchmarkCode1
M3oE: Multi-Domain Multi-Task Mixture-of Experts Recommendation FrameworkCode1
LLM Guided Evolution - The Automation of Models Advancing ModelsCode1
Robustifying and Boosting Training-Free Neural Architecture SearchCode1
AutoMMLab: Automatically Generating Deployable Models from Language Instructions for Computer Vision TasksCode1
Retrieve, Merge, Predict: Augmenting Tables with Data LakesCode1
Is Mamba Capable of In-Context Learning?Code1
auto-sktime: Automated Time Series ForecastingCode1
STREAMLINE: An Automated Machine Learning Pipeline for Biomedicine Applied to Examine the Utility of Photography-Based Phenotypes for OSA Prediction Across International Sleep CentersCode1
Embedding in Recommender Systems: A SurveyCode1
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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