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 591600 of 641 papers

TitleStatusHype
Deep Architecture Connectivity Matters for Its Convergence: A Fine-Grained AnalysisCode0
Confidence Interval Estimation of Predictive Performance in the Context of AutoMLCode0
Auto-Keras: An Efficient Neural Architecture Search SystemCode0
ML-Plan: Automated machine learning via hierarchical planningCode0
Comparison of Automated Machine Learning Tools for SMS Spam Message FilteringCode0
Clairvoyance: A Pipeline Toolkit for Medical Time SeriesCode0
Bridging the Gap of AutoGraph between Academia and Industry: Analysing AutoGraph Challenge at KDD Cup 2020Code0
Towards Model Selection using Learning Curve Cross-ValidationCode0
Auto-FP: An Experimental Study of Automated Feature Preprocessing for Tabular DataCode0
SAFE ML: Surrogate Assisted Feature Extraction for Model LearningCode0
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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