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 101125 of 641 papers

TitleStatusHype
Deep Fast Vision: Accelerated Deep Transfer Learning Vision Prototyping and BeyondCode1
DHP: Differentiable Meta Pruning via HyperNetworksCode1
Empirical Analysis of Model Selection for Heterogeneous Causal Effect EstimationCode1
Cross-Modal Fine-Tuning: Align then RefineCode1
DARTS-: Robustly Stepping out of Performance Collapse Without IndicatorsCode1
I-MCTS: Enhancing Agentic AutoML via Introspective Monte Carlo Tree SearchCode1
CliMB: An AI-enabled Partner for Clinical Predictive ModelingCode1
Automating Outlier Detection via Meta-LearningCode1
Construction of Hierarchical Neural Architecture Search Spaces based on Context-free GrammarsCode1
Learning meta-features for AutoMLCode1
DC-BENCH: Dataset Condensation BenchmarkCode1
LLM Guided Evolution - The Automation of Models Advancing ModelsCode1
Automated Machine Learning in InsuranceCode1
M3oE: Multi-Domain Multi-Task Mixture-of Experts Recommendation FrameworkCode1
Cardea: An Open Automated Machine Learning Framework for Electronic Health RecordsCode1
CATE: Computation-aware Neural Architecture Encoding with TransformersCode1
Bi-level Alignment for Cross-Domain Crowd CountingCode1
Architecture Disentanglement for Deep Neural NetworksCode1
Deep AutoAugmentCode1
MixConv: Mixed Depthwise Convolutional KernelsCode1
Bag of Baselines for Multi-objective Joint Neural Architecture Search and Hyperparameter OptimizationCode1
AutoVideo: An Automated Video Action Recognition SystemCode1
auto-sktime: Automated Time Series ForecastingCode1
ARLBench: Flexible and Efficient Benchmarking for Hyperparameter Optimization in Reinforcement LearningCode1
AutoSmart: An Efficient and Automatic Machine Learning framework for Temporal Relational DataCode1
Show:102550
← PrevPage 5 of 26Next →

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