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 401410 of 641 papers

TitleStatusHype
Privacy-preserving Online AutoML for Domain-Specific Face Detection0
Model-free feature selection to facilitate automatic discovery of divergent subgroups in tabular data0
Automated Machine Learning: A Case Study on Non-Intrusive Appliance Load Monitoring0
AutoCl : A Visual Interactive System for Automatic Deep Learning Classifier Recommendation Based on Models Performance0
Mining Robust Default Configurations for Resource-constrained AutoML0
SapientML: Synthesizing Machine Learning Pipelines by Learning from Human-Written Solutions0
Review of automated time series forecasting pipelines0
NAS-Bench-Suite: NAS Evaluation is (Now) Surprisingly Easy0
FRAMED: An AutoML Approach for Structural Performance Prediction of Bicycle Frames0
Online AutoML: An adaptive AutoML framework for online learning0
Show:102550
← PrevPage 41 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