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BIG-bench Machine Learning

This branch include most common machine learning fundamental algorithms.

Papers

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Showing 276–300 of 10033 papers

TitleStatusHype
Augmenting DL with Adversarial Training for Robust Prediction of Epilepsy SeizuresCode1
Atomic structure generation from reconstructing structural fingerprintsCode1
Asymmetric Private Set Intersection with Applications to Contact Tracing and Private Vertical Federated Machine LearningCode1
Attacks on Image Encryption Schemes for Privacy-Preserving Deep Neural NetworksCode1
A Unified View of Relational Deep Learning for Drug Pair ScoringCode1
A Survey of Machine Learning Techniques in Adversarial Image ForensicsCode1
Open Source Software for Efficient and Transparent ReviewsCode1
A Survey of Privacy Attacks in Machine LearningCode1
Are We Really Making Much Progress? A Worrying Analysis of Recent Neural Recommendation ApproachesCode1
A Review of the Gumbel-max Trick and its Extensions for Discrete Stochasticity in Machine LearningCode1
Artistic Style in Robotic Painting; a Machine Learning Approach to Learning Brushstroke from Human ArtistsCode1
A Data-Centric Optimization Framework for Machine LearningCode1
Achieving Fairness at No Utility Cost via Data Reweighing with InfluenceCode1
A Distributed Trust Framework for Privacy-Preserving Machine LearningCode1
A semi-agnostic ansatz with variable structure for quantum machine learningCode1
A simple equivariant machine learning method for dynamics based on scalarsCode1
A smile is all you need: Predicting limiting activity coefficients from SMILES with natural language processingCode1
A survey of bias in Machine Learning through the prism of Statistical Parity for the Adult Data SetCode1
A Survey of Label-noise Representation Learning: Past, Present and FutureCode1
A Survey on Machine Learning Algorithms for Applications in Cognitive Radio NetworksCode1
A Survey on Machine Learning Techniques for Source Code AnalysisCode1
A survey on datasets for fairness-aware machine learningCode1
AutoCLINT: The Winning Method in AutoCV Challenge 2019Code1
Auditing Differentially Private Machine Learning: How Private is Private SGD?Code1
AutoSmart: An Efficient and Automatic Machine Learning framework for Temporal Relational DataCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Fb232account and password 100—Unverified