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 371380 of 641 papers

TitleStatusHype
Man versus Machine: AutoML and Human Experts' Role in Phishing Detection0
An Information Theory-inspired Strategy for Automatic Network PruningCode1
AutoVideo: An Automated Video Action Recognition SystemCode1
AMDet: A Tool for Mitotic Cell Detection in Histopathology SlidesCode0
AutoML Meets Time Series Regression Design and Analysis of the AutoSeries ChallengeCode0
Benchmarking AutoML Frameworks for Disease Prediction Using Medical Claims0
Incorporating domain knowledge into neural-guided search0
VolcanoML: Speeding up End-to-End AutoML via Scalable Search Space DecompositionCode1
Federated Whole Prostate Segmentation in MRI with Personalized Neural Architectures0
The Power of Proxy Data and Proxy Networks for Hyper-Parameter Optimization in Medical Image Segmentation0
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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