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 111120 of 641 papers

TitleStatusHype
An Information Theory-inspired Strategy for Automatic Network PruningCode1
AutoVideo: An Automated Video Action Recognition SystemCode1
VolcanoML: Speeding up End-to-End AutoML via Scalable Search Space DecompositionCode1
Bilinear Scoring Function Search for Knowledge Graph LearningCode1
Automated Machine Learning Techniques for Data StreamsCode1
You Only Compress Once: Towards Effective and Elastic BERT Compression via Exploit-Explore Stochastic Nature GradientCode1
Multimodal AutoML on Structured Tables with Text FieldsCode1
Bag of Baselines for Multi-objective Joint Neural Architecture Search and Hyperparameter OptimizationCode1
Efficient Relation-aware Scoring Function Search for Knowledge Graph EmbeddingCode1
Search to aggregate neighborhood for graph neural networkCode1
Show:102550
← PrevPage 12 of 65Next →

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