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 441–450 of 641 papers

TitleStatusHype
SapientML: Synthesizing Machine Learning Pipelines by Learning from Human-Written Solutions—0
Scalable End-to-End ML Platforms: from AutoML to Self-serve—0
Scaling Gaussian Processes for Learning Curve Prediction via Latent Kronecker Structure—0
SEAL: Searching Expandable Architectures for Incremental Learning—0
Search-based Methods for Multi-Cloud Configuration—0
Searching to Exploit Memorization Effect in Learning with Noisy Labels—0
SELA: Tree-Search Enhanced LLM Agents for Automated Machine Learning—0
Selecting Optimal Trace Clustering Pipelines with AutoML—0
Semantic-Based Neural Network Repair—0
Sequential Automated Machine Learning: Bandits-driven Exploration using a Collaborative Filtering Representation—0
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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