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 331340 of 641 papers

TitleStatusHype
AutoML-GPT: Automatic Machine Learning with GPT0
Benchmarking Automated Machine Learning Methods for Price Forecasting Applications0
Constructing a meta-learner for unsupervised anomaly detection0
Complex Mixer for MedMNIST Classification Decathlon0
eTOP: Early Termination of Pipelines for Faster Training of AutoML Systems0
AutoRL Hyperparameter LandscapesCode0
Classification of integers based on residue classes via modern deep learning algorithmsCode0
Multi-Microgrid Collaborative Optimization Scheduling Using an Improved Multi-Agent Soft Actor-Critic Algorithm0
Synthesis of Mathematical programs from Natural Language Specifications0
Efficient Multi-stage Inference on Tabular Data0
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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