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 151175 of 641 papers

TitleStatusHype
DC-BENCH: Dataset Condensation BenchmarkCode1
Deep AutoAugmentCode1
Construction of Hierarchical Neural Architecture Search Spaces based on Context-free GrammarsCode1
Cross-Modal Fine-Tuning: Align then RefineCode1
Hyperparameter optimization in deep multi-target predictionCode1
Hyperparameter Optimization via Sequential Uniform DesignsCode1
Bilinear Scoring Function Search for Knowledge Graph LearningCode1
CliMB: An AI-enabled Partner for Clinical Predictive ModelingCode1
DARTS-: Robustly Stepping out of Performance Collapse Without IndicatorsCode1
Deep-n-Cheap: An Automated Search Framework for Low Complexity Deep LearningCode1
Bi-level Alignment for Cross-Domain Crowd CountingCode1
LEMUR Neural Network Dataset: Towards Seamless AutoMLCode1
OMPQ: Orthogonal Mixed Precision QuantizationCode1
AutoDC: Automated data-centric processingCode1
Automatic Discovery of Heterogeneous Machine Learning Pipelines: An Application to Natural Language Processing0
Automatic deep learning for trend prediction in time series data0
Automatic Componentwise Boosting: An Interpretable AutoML System0
Automated Reinforcement Learning (AutoRL): A Survey and Open Problems0
Automated Phytosensing: Ozone Exposure Classification Based on Plant Electrical Signals0
Exploring the Intersection between Neural Architecture Search and Continual Learning0
Automated Multi-Label Classification based on ML-Plan0
Automated Model Compression by Jointly Applied Pruning and Quantization0
Are Large Language Models the New Interface for Data Pipelines?0
CascadeML: An Automatic Neural Network Architecture Evolution and Training Algorithm for Multi-label Classification0
Chameleon: A Semi-AutoML framework targeting quick and scalable development and deployment of production-ready ML systems for SMEs0
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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