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 441450 of 641 papers

TitleStatusHype
AutoML-GPT: Automatic Machine Learning with GPT0
AutoML-GPT: Large Language Model for AutoML0
AutoML in the Age of Large Language Models: Current Challenges, Future Opportunities and Risks0
AutoML in The Wild: Obstacles, Workarounds, and Expectations0
AutoML @ NeurIPS 2018 challenge: Design and Results0
AutoML Strategy Based on Grammatical Evolution: A Case Study about Knowledge Discovery from Text0
AutoML Systems For Medical Imaging0
AutoML to generate ensembles of deep neural networks0
AutoCP: Automated Pipelines for Accurate Prediction Intervals0
AutoPDL: Automatic Prompt Optimization for LLM Agents0
Show:102550
← PrevPage 45 of 65Next →

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