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 131140 of 641 papers

TitleStatusHype
MobileVLM V2: Faster and Stronger Baseline for Vision Language ModelCode5
Is Mamba Capable of In-Context Learning?Code1
Grammar-based evolutionary approach for automated workflow composition with domain-specific operators and ensemble diversity0
Large Language Model Agent for Hyper-Parameter Optimization0
Information Leakage Detection through Approximate Bayes-optimal PredictionCode0
X Hacking: The Threat of Misguided AutoMLCode0
DREAM: Debugging and Repairing AutoML Pipelines0
KAXAI: An Integrated Environment for Knowledge Analysis and Explainable AI0
MobileVLM : A Fast, Strong and Open Vision Language Assistant for Mobile DevicesCode3
Integration Of Evolutionary Automated Machine Learning With Structural Sensitivity Analysis For Composite Pipelines0
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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