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 126150 of 641 papers

TitleStatusHype
Shape Adaptor: A Learnable Resizing ModuleCode1
KGLiDS: A Platform for Semantic Abstraction, Linking, and Automation of Data ScienceCode1
Mamba4Cast: Efficient Zero-Shot Time Series Forecasting with State Space ModelsCode1
Bilinear Scoring Function Search for Knowledge Graph LearningCode1
Is Mamba Capable of In-Context Learning?Code1
Learning meta-features for AutoMLCode1
I-MCTS: Enhancing Agentic AutoML via Introspective Monte Carlo Tree SearchCode1
AutoML: A Survey of the State-of-the-ArtCode1
auto-sktime: Automated Time Series ForecastingCode1
LEMUR Neural Network Dataset: Towards Seamless AutoMLCode1
AutoML Two-Sample TestCode1
Automating Outlier Detection via Meta-LearningCode1
AutoProteinEngine: A Large Language Model Driven Agent Framework for Multimodal AutoML in Protein EngineeringCode1
AutoML Segmentation for 3D Medical Image Data: Contribution to the MSD Challenge 2018Code1
HPOBench: A Collection of Reproducible Multi-Fidelity Benchmark Problems for HPOCode1
Hyperparameter optimization in deep multi-target predictionCode1
Large Language Models for Automated Data Science: Introducing CAAFE for Context-Aware Automated Feature EngineeringCode1
GAMA: a General Automated Machine learning AssistantCode1
AutoSmart: An Efficient and Automatic Machine Learning framework for Temporal Relational DataCode1
AutoMMLab: Automatically Generating Deployable Models from Language Instructions for Computer Vision TasksCode1
AutoVideo: An Automated Video Action Recognition SystemCode1
FLAML: A Fast and Lightweight AutoML LibraryCode1
Hyperparameter Optimization via Sequential Uniform DesignsCode1
LLM Guided Evolution - The Automation of Models Advancing ModelsCode1
MetaPoison: Practical General-purpose Clean-label Data PoisoningCode1
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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