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BIG-bench Machine Learning

This branch include most common machine learning fundamental algorithms.

Papers

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Showing 751–775 of 10033 papers

TitleStatusHype
A Model-Driven Approach to Machine Learning and Software Modeling for the IoTCode1
CryptGPU: Fast Privacy-Preserving Machine Learning on the GPUCode1
Crystal structure prediction with machine learning-based element substitutionCode1
Cyber Attack Detection thanks to Machine Learning AlgorithmsCode1
Evaluation and Optimization of Distributed Machine Learning Techniques for Internet of ThingsCode1
Cyberbullying Detection with Fairness ConstraintsCode1
DagSim: Combining DAG-based model structure with unconstrained data types and relations for flexible, transparent, and modularized data simulationCode1
Cyclic Boosting -- an explainable supervised machine learning algorithmCode1
Equivariant Graph Neural Networks for 3D Macromolecular StructureCode1
Production of Categorical Data Verifying Differential Privacy: Conception and Applications to Machine LearningCode1
A Review of the Gumbel-max Trick and its Extensions for Discrete Stochasticity in Machine LearningCode1
DaST: Data-free Substitute Training for Adversarial AttacksCode1
Data Curation and Quality Assurance for Machine Learning-based Cyber Intrusion DetectionCode1
Data Debugging with Shapley Importance over End-to-End Machine Learning PipelinesCode1
Ergo, SMIRK is Safe: A Safety Case for a Machine Learning Component in a Pedestrian Automatic Emergency Brake SystemCode1
Pseudo Random Number Generation: a Reinforcement Learning approachCode1
Dataset Optimization Strategies for MalwareTraffic DetectionCode1
An empirical evaluation of active inference in multi-armed banditsCode1
Leakage of Dataset Properties in Multi-Party Machine LearningCode1
Dataset Inference: Ownership Resolution in Machine LearningCode1
A Multimodal Machine Learning Framework for Teacher Vocal Delivery EvaluationCode1
A Comprehensive Review on Non-Neural Networks Collaborative Filtering Recommendation SystemsCode1
Datasheets for DatasetsCode1
Coresets for Data-efficient Training of Machine Learning ModelsCode1
Analyzing Koopman approaches to physics-informed machine learning for long-term sea-surface temperature forecastingCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Fb232account and password 100—Unverified