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 261270 of 641 papers

TitleStatusHype
TC-SKNet with GridMask for Low-complexity Classification of Acoustic scene0
Efficient Non-Parametric Optimizer Search for Diverse TasksCode0
Automatic and effective discovery of quantum kernelsCode0
Industrial Data Science for Batch Manufacturing Processes0
IoT Data Analytics in Dynamic Environments: From An Automated Machine Learning PerspectiveCode2
MDE for Machine Learning-Enabled Software Systems: A Case Study and Comparison of MontiAnna & ML-Quadrat0
Fraud Dataset Benchmark and ApplicationsCode2
A Deep Neural Networks ensemble workflow from hyperparameter search to inference leveraging GPU clusters0
An Empirical Study on the Usage of Automated Machine Learning ToolsCode0
Task Selection for AutoML System Evaluation0
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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