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Fairness

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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://bitbucket.org/elisaferrari/fbi-loss-code

공식 코드

Addressing Fairness, Bias and Class Imbalance in Machine Learning: the FBI-loss

https://bitbucket.org/emird/murtree

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MurTree: Optimal Classification Trees via Dynamic Programming and Search

https://bitbucket.org/nelliottrosa/base_fairness

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A Differentiable Distance Approximation for Fairer Image Classification

https://bitbucket.org/uwtppml/privfair

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PrivFair: a Library for Privacy-Preserving Fairness Auditing

https://github.com/13543024276/fairsort

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FairSort: Learning to Fair Rank for Personalized Recommendations in Two-Sided Platforms

https://github.com/18jeffreyma/afl-bench

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FedStaleWeight: Buffered Asynchronous Federated Learning with Fair Aggregation via Staleness Reweighting

https://github.com/514flowey/jdet-cobb

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Theoretically Achieving Continuous Representation of Oriented Bounding Boxes

https://github.com/99Catherine99/peer-induced-fairness

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Peer-induced Fairness: A Causal Approach for Algorithmic Fairness Auditing

https://github.com/AI-secure/KNN-PVLDB

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Efficient Task-Specific Data Valuation for Nearest Neighbor Algorithms

https://github.com/AIasd/noise_fairlearn

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Noise-tolerant fair classification

https://github.com/ALEX-nlp/MUI-Eval

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Model Utility Law: Evaluating LLMs beyond Performance through Mechanism Interpretable Metric

https://github.com/ATriantafyllopoulos/enrollment-personalization

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Enrolment-based personalisation for improving individual-level fairness in speech emotion recognition

https://github.com/Abigale001/FairDGE

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Toward Structure Fairness in Dynamic Graph Embedding: A Trend-aware Dual Debiasing Approach

https://github.com/Abrar2652/Network-Intrusion-Detection

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CAGN-GAT Fusion: A Hybrid Contrastive Attentive Graph Neural Network for Network Intrusion Detection

https://github.com/AdrianArnaiz/fair-shap

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Towards Algorithmic Fairness by means of Instance-level Data Re-weighting based on Shapley Values

https://github.com/Ahmadreza401/fair_influen_max

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Adversarial Graph Embeddings for Fair Influence Maximization over Social Networks

https://github.com/AhmedImtiazPrio/MaGNET

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MaGNET: Uniform Sampling from Deep Generative Network Manifolds Without Retraining

https://github.com/AlexandreBinninger/TetWeave

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TetWeave: Isosurface Extraction using On-The-Fly Delaunay Tetrahedral Grids for Gradient-Based Mesh Optimization

https://github.com/Alexkael/CONFUSIONAL-SPECTRAL-REGULARIZATION

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Enhancing Robust Fairness via Confusional Spectral Regularization

https://github.com/Amaodemao/BiasPainter

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New Job, New Gender? Measuring the Social Bias in Image Generation Models

https://github.com/AnayMehrotra/Fair-Online-Advertising

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Toward Controlling Discrimination in Online Ad Auctions

https://github.com/AnayMehrotra/Fair-classification-with-adversarial-perturbations

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Fair Classification with Adversarial Perturbations

https://github.com/AnayMehrotra/Noisy-Fair-Subset-Selection

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Mitigating Bias in Set Selection with Noisy Protected Attributes

https://github.com/Antimony5292/CILIATE

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CILIATE: Towards Fairer Class-based Incremental Learning by Dataset and Training Refinement

https://github.com/Antimony5292/FairNeuron

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FairNeuron: Improving Deep Neural Network Fairness with Adversary Games on Selective Neurons

https://github.com/Arstanley/Awesome-Trustworthy-Retrieval-Augmented-Generation

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Towards Trustworthy Retrieval Augmented Generation for Large Language Models: A Survey

https://github.com/Auto-Arena/Auto-Arena-LLMs

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Auto-Arena: Automating LLM Evaluations with Agent Peer Battles and Committee Discussions

https://github.com/AvivNavon/pareto-hypernetworks

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Learning the Pareto Front with Hypernetworks

https://github.com/BeanHam/interpretable-machine-learning

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In Pursuit of Interpretable, Fair and Accurate Machine Learning for Criminal Recidivism Prediction

https://github.com/Bearwithchris/Fair-Generative-Model-via-Transfer-Learning

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Fair Generative Models via Transfer Learning

https://github.com/Bearwithchris/Fairness_Metric

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Measuring Fairness in Generative Models

https://github.com/BehroozRazeghi/CLUB

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Bottlenecks CLUB: Unifying Information-Theoretic Trade-offs Among Complexity, Leakage, and Utility

https://github.com/BiDAlab/DiveFace

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SensitiveNets: Learning Agnostic Representations with Application to Face Images

https://github.com/BiDAlab/FairCVtest

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Human-Centric Multimodal Machine Learning: Recent Advances and Testbed on AI-based Recruitment

https://github.com/BioIntelligence-Lab/VAE-Adversarial-Debiasing

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Towards Fair Medical AI: Adversarial Debiasing of 3D CT Foundation Embeddings

https://github.com/BobbyZhouZijian/ProbablyApproximateShapleyFairness

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Probably Approximate Shapley Fairness with Applications in Machine Learning

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