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 431440 of 641 papers

TitleStatusHype
AutoML-based Almond Yield Prediction and Projection in California0
AutoML-Based Drought Forecast with Meteorological Variables0
AutoMLBench: A Comprehensive Experimental Evaluation of Automated Machine Learning Frameworks0
AutoML Benchmark with shorter time constraints and early stopping0
Auto-ML Deep Learning for Rashi Scripts OCR0
AutoML for Contextual Bandits0
AutoML for Deep Recommender Systems: A Survey0
AutoML for Large Capacity Modeling of Meta's Ranking Systems0
AutoML for Multilayer Perceptron and FPGA Co-design0
AutoML from Service Provider's Perspective: Multi-device, Multi-tenant Model Selection with GP-EI0
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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