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BIG-bench Machine Learning

This branch include most common machine learning fundamental algorithms.

Papers

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Showing 76–100 of 10033 papers

TitleStatusHype
Fast inference of deep neural networks in FPGAs for particle physicsCode2
Foolbox: A Python toolbox to benchmark the robustness of machine learning modelsCode2
Fused Gromov-Wasserstein distance for structured objects: theoretical foundations and mathematical propertiesCode2
HierarchicalForecast: A Reference Framework for Hierarchical Forecasting in PythonCode2
hls4ml: An Open-Source Codesign Workflow to Empower Scientific Low-Power Machine Learning DevicesCode2
Deep Reinforcement Learning for Multi-Agent InteractionCode2
Decision-Based Adversarial Attacks: Reliable Attacks Against Black-Box Machine Learning ModelsCode2
CrypTen: Secure Multi-Party Computation Meets Machine LearningCode2
Connections between Relational Event Model and Inverse Reinforcement Learning for Characterizing Group Interaction SequencesCode2
MACE: An Efficient Model-Agnostic Framework for Counterfactual ExplanationCode2
Machine Learning in Asset Management—Part 1: Portfolio Construction—Trading StrategiesCode2
auton-survival: an Open-Source Package for Regression, Counterfactual Estimation, Evaluation and Phenotyping with Censored Time-to-Event DataCode2
Bayesian Optimization is Superior to Random Search for Machine Learning Hyperparameter Tuning: Analysis of the Black-Box Optimization Challenge 2020Code2
Frugal Optimization for Cost-related HyperparametersCode2
Monitoring and explainability of models in productionCode2
On Hyperparameter Optimization of Machine Learning Algorithms: Theory and PracticeCode2
Designing Inherently Interpretable Machine Learning ModelsCode2
Graph Data Augmentation for Graph Machine Learning: A SurveyCode2
Adversarial Robustness for CodeCode1
Asymmetric Private Set Intersection with Applications to Contact Tracing and Private Vertical Federated Machine LearningCode1
A Survey on Machine Learning Algorithms for Applications in Cognitive Radio NetworksCode1
AdViCE: Aggregated Visual Counterfactual Explanations for Machine Learning Model ValidationCode1
A Survey on Machine Learning Techniques for Source Code AnalysisCode1
A Survey of Machine Learning Techniques in Adversarial Image ForensicsCode1
A survey on Adversarial Recommender Systems: from Attack/Defense strategies to Generative Adversarial NetworksCode1
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Benchmark Results

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1Fb232account and password 100—Unverified