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 271280 of 641 papers

TitleStatusHype
AutoQ: Automated Kernel-Wise Neural Network Quantization0
AutoEmb: Automated Embedding Dimensionality Search in Streaming Recommendations0
AutoPruning for Deep Neural Network with Dynamic Channel Masking0
AutoDS: Towards Human-Centered Automation of Data Science0
An AutoML-based approach for Network Intrusion Detection0
AutoPINN: When AutoML Meets Physics-Informed Neural Networks0
AutoPDL: Automatic Prompt Optimization for LLM Agents0
AutoDOViz: Human-Centered Automation for Decision Optimization0
Application of an automated machine learning-genetic algorithm (AutoML-GA) coupled with computational fluid dynamics simulations for rapid engine design optimization0
AutoCP: Automated Pipelines for Accurate Prediction Intervals0
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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