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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 111–120 of 641 papers

TitleStatusHype
Neural Architecture Search for Sentence Classification with BERTCode0
Automated Contrastive Learning Strategy Search for Time Series—0
Deciphering AutoML Ensembles: cattleia's Assistance in Decision-Making—0
LLM Guided Evolution - The Automation of Models Advancing ModelsCode1
Automated data processing and feature engineering for deep learning and big data applications: a survey—0
Data augmentation with automated machine learning: approaches and performance comparison with classical data augmentation methods—0
Robustifying and Boosting Training-Free Neural Architecture SearchCode1
Automated Machine Learning for Multi-Label Classification—0
Evolving machine learning workflows through interactive AutoML—0
Principled Architecture-aware Scaling of HyperparametersCode0
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All datasetsChalearn-AutoML-1Breast Cancer Coimbra Data SetOrdinalDatasetWine

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1marc.boulleRank (AutoML5)6.4—Unverified
2reference_mbRank (AutoML5)5.2—Unverified
3postech.mlg_exbrainRank (AutoML5)5.2—Unverified
4abhishek4Rank (AutoML5)4.6—Unverified
5referenceRank (AutoML5)4.4—Unverified
6reference_lsRank (AutoML5)4—Unverified
7djajeticRank (AutoML5)3—Unverified
8aad_freiburgRank (AutoML5)1.6—Unverified
#ModelMetricClaimedVerifiedStatus
1Logistic RegressionAccuracy97.02—Unverified
#ModelMetricClaimedVerifiedStatus
1Zero-shot-BERT-SORT1:1 Accuracy55—Unverified
#ModelMetricClaimedVerifiedStatus
1Logistic Regressionaccuracy98.33—Unverified