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 461–470 of 641 papers

TitleStatusHype
Sequential Automated Machine Learning: Bandits-driven Exploration using a Collaborative Filtering Representation—0
Towards Model Selection using Learning Curve Cross-ValidationCode0
AutoML Adoption in ML Software—0
Replacing the Ex-Def Baseline in AutoML by Naive AutoML—0
Automating Data Science: Prospects and Challenges—0
Chameleon: A Semi-AutoML framework targeting quick and scalable development and deployment of production-ready ML systems for SMEs—0
Model LineUpper: Supporting Interactive Model Comparison at Multiple Levels for AutoML—0
How Powerful are Performance Predictors in Neural Architecture Search?—0
Bit-Mixer: Mixed-precision networks with runtime bit-width selection—0
Naive Automated Machine Learning -- A Late Baseline for AutoML—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