:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Jin, Youngmi, Gim, Jio, Lee, Tae-Jin, Suh, Young-Joo
Format:	Preprint
Published:	2022
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2202.11966
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Maestro-EVC: Controllable Emotional Voice Conversion Guided by References and Explicit Prosody
by: Yoon, Jinsung, et al.
Published: (2025)

On the (In)Compatibility between Group Fairness and Individual Fairness
by: Xu, Shizhou, et al.
Published: (2024)

Fair Play for Individuals, Foul Play for Groups? Auditing Anonymization's Impact on ML Fairness
by: Arcolezi, Héber H., et al.
Published: (2025)

Fair Recourse for All: Ensuring Individual and Group Fairness in Counterfactual Explanations
by: Ezzeddine, Fatima, et al.
Published: (2026)

Bridging the Fairness Divide: Achieving Group and Individual Fairness in Graph Neural Networks
by: Zhan, Duna, et al.
Published: (2024)

Constructing Fair Latent Space for Intersection of Fairness and Explainability
by: Joo, Hyungjun, et al.
Published: (2024)

FairExpand: Individual Fairness on Graphs with Partial Similarity Information
by: Salganik, Rebecca, et al.
Published: (2025)

Monotone Individual Fairness
by: Bechavod, Yahav
Published: (2024)

FairAD: Computationally Efficient Fair Graph Clustering via Algebraic Distance
by: Vuong, Minh Phu, et al.
Published: (2025)

GRAPHGINI: Fostering Individual and Group Fairness in Graph Neural Networks
by: Sirohi, Anuj Kumar, et al.
Published: (2024)

Alternatives to the Laplacian for Scalable Spectral Clustering with Group Fairness Constraints
by: Ojeda-Ruiz, Iván, et al.
Published: (2025)

Equalised Odds is not Equal Individual Odds: Post-processing for Group and Individual Fairness
by: Small, Edward A., et al.
Published: (2023)

Individual Fairness In Strategic Classification
by: Zuo, Zhiqun, et al.
Published: (2026)

FFB: A Fair Fairness Benchmark for In-Processing Group Fairness Methods
by: Han, Xiaotian, et al.
Published: (2023)

Causal Fair Metric: Bridging Causality, Individual Fairness, and Adversarial Robustness
by: Ehyaei, Ahmad-Reza, et al.
Published: (2023)

FairRR: Pre-Processing for Group Fairness through Randomized Response
by: Zeng, Xianli, et al.
Published: (2024)

Generalizing Fair Clustering to Multiple Groups: Algorithms and Applications
by: Chakraborty, Diptarka, et al.
Published: (2025)

Merging Methods for Multilingual Knowledge Editing for Large Language Models: An Empirical Odyssey
by: Lee, Kunil, et al.
Published: (2026)

From Pseudorandomness to Multi-Group Fairness and Back
by: Dwork, Cynthia, et al.
Published: (2023)

Rethinking Individual Fairness in Deepfake Detection
by: Hou, Aryana, et al.
Published: (2025)

Evaluating AI Group Fairness: a Fuzzy Logic Perspective
by: Krasanakis, Emmanouil, et al.
Published: (2024)

Entropy-driven Fair and Effective Federated Learning
by: Wang, Lin, et al.
Published: (2023)

On the Maximal Local Disparity of Fairness-Aware Classifiers
by: Jin, Jinqiu, et al.
Published: (2024)

Toward Unifying Group Fairness Evaluation from a Sparsity Perspective
by: Sheng, Zhecheng, et al.
Published: (2025)

Trade-offs Between Individual and Group Fairness in Machine Learning: A Comprehensive Review
by: Benítez-Peña, Sandra, et al.
Published: (2026)

FairWire: Fair Graph Generation
by: Kose, O. Deniz, et al.
Published: (2024)

Minimax Group Fairness in Strategic Classification
by: Diana, Emily, et al.
Published: (2024)

Fair Anomaly Detection For Imbalanced Groups
by: Wu, Ziwei, et al.
Published: (2024)

Algorithmic Fairness in Performative Policy Learning: Escaping the Impossibility of Group Fairness
by: Somerstep, Seamus, et al.
Published: (2024)

Are Your Models Still Fair? Fairness Attacks on Graph Neural Networks via Node Injections
by: Luo, Zihan, et al.
Published: (2024)

Testing Individual Fairness in Graph Neural Networks
by: Nasiri, Roya
Published: (2025)

Individual Fairness Through Reweighting and Tuning
by: Mahamadou, Abdoul Jalil Djiberou, et al.
Published: (2024)

FairDICE: Fairness-Driven Offline Multi-Objective Reinforcement Learning
by: Kim, Woosung, et al.
Published: (2025)

Bayes-Optimal Classifiers under Group Fairness
by: Zeng, Xianli, et al.
Published: (2022)

On the Alignment of Group Fairness with Attribute Privacy
by: Aalmoes, Jan, et al.
Published: (2022)

Migrate Demographic Group For Fair GNNs
by: Hu, YanMing, et al.
Published: (2023)

BadFair: Backdoored Fairness Attacks with Group-conditioned Triggers
by: Xue, Jiaqi, et al.
Published: (2024)

FairFedMed: Benchmarking Group Fairness in Federated Medical Imaging with FairLoRA
by: Li, Minghan, et al.
Published: (2025)

GFairHint: Improving Individual Fairness for Graph Neural Networks via Fairness Hint
by: Xu, Paiheng, et al.
Published: (2023)

pFedFair: Towards Optimal Group Fairness-Accuracy Trade-off in Heterogeneous Federated Learning
by: Lei, Haoyu, et al.
Published: (2025)