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BIG-bench Machine Learning

This branch include most common machine learning fundamental algorithms.

Papers

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Showing 4876–4900 of 10033 papers

TitleStatusHype
Tropical and Extratropical Cyclone Detection Using Deep Learning—0
Throwing Darts in the Dark? Detecting Bots with Limited Data using Neural Data Augmentation—0
Insights into Performance Fitness and Error Metrics for Machine Learning—0
DiscretizationNet: A Machine-Learning based solver for Navier-Stokes Equations using Finite Volume Discretization—0
Marginal likelihood computation for model selection and hypothesis testing: an extensive review—0
Impact studies of nationwide measures COVID-19 anti-pandemic: compartmental model and machine learning—0
Usage of Network Simulators in Machine-Learning-Assisted 5G/6G NetworksCode1
Machine Learning for Exploring Spatial Affordance Patterns—0
NeuroAttack: Undermining Spiking Neural Networks Security through Externally Triggered Bit-Flips—0
Arabic Offensive Language Detection Using Machine Learning and Ensemble Machine Learning Approaches—0
Forecasting with sktime: Designing sktime's New Forecasting API and Applying It to Replicate and Extend the M4 StudyCode1
How to Learn from Others: Transfer Machine Learning with Additive Regression Models to Improve Sales Forecasting—0
A flexible, extensible software framework for model compression based on the LC algorithm—0
Guided interactive image segmentation using machine learning and color based data set clustering—0
Quantum-Classical Machine learning by Hybrid Tensor NetworksCode0
Uncovering Gender Bias in Media Coverage of Politicians with Machine Learning—0
How to Make 5G Communications "Invisible": Adversarial Machine Learning for Wireless Privacy—0
Evaluating and Improving Adversarial Robustness of Machine Learning-Based Network Intrusion DetectorsCode1
Participatory Problem Formulation for Fairer Machine Learning Through Community Based System Dynamics—0
Cross-lingual Transfer of Sentiment Classifiers—0
Manthan: A Data Driven Approach for Boolean Function SynthesisCode1
Ethical Adversaries: Towards Mitigating Unfairness with Adversarial Machine LearningCode1
MixML: A Unified Analysis of Weakly Consistent Parallel Learning—0
Mitigating Gender Bias in Machine Learning Data Sets—0
Performance evaluation of Machine learning algorithms in Biomedical Document ClassificationCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Fb232account and password 100—Unverified