Fair Sampling in Diffusion Models through Switching Mechanism
Fuente:
arXiv
Saved in:
| Main Authors: | Choi, Yujin, Park, Jinseong, Kim, Hoki, Lee, Jaewook, Park, Saerom |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Stability Analysis of Sharpness-Aware Minimization
by: Kim, Hoki, et al.
Published: (2023)
by: Kim, Hoki, et al.
Published: (2023)
BayesNAM: Leveraging Inconsistency for Reliable Explanations
by: Kim, Hoki, et al.
Published: (2024)
by: Kim, Hoki, et al.
Published: (2024)
Leveraging Programmatically Generated Synthetic Data for Differentially Private Diffusion Training
by: Choi, Yujin, et al.
Published: (2024)
by: Choi, Yujin, et al.
Published: (2024)
Are Self-Attentions Effective for Time Series Forecasting?
by: Kim, Dongbin, et al.
Published: (2024)
by: Kim, Dongbin, et al.
Published: (2024)
Multi-Class Support Vector Machine with Differential Privacy
by: Park, Jinseong, et al.
Published: (2025)
by: Park, Jinseong, et al.
Published: (2025)
TimeBridge: Better Diffusion Prior Design with Bridge Models for Time Series Generation
by: Park, Jinseong, et al.
Published: (2024)
by: Park, Jinseong, et al.
Published: (2024)
Safeguarding Privacy of Retrieval Data against Membership Inference Attacks: Is This Query Too Close to Home?
by: Choi, Yujin, et al.
Published: (2025)
by: Choi, Yujin, et al.
Published: (2025)
Machine Unlearning for Masked Diffusion Language Models
by: Lee, Georu, et al.
Published: (2026)
by: Lee, Georu, et al.
Published: (2026)
Data Unlearning Beyond Uniform Forgetting via Diffusion Time and Frequency Selection
by: Park, Jinseong, et al.
Published: (2025)
by: Park, Jinseong, et al.
Published: (2025)
Improving the Utility of Differentially Private Clustering through Dynamical Processing
by: Byun, Junyoung, et al.
Published: (2023)
by: Byun, Junyoung, et al.
Published: (2023)
Counterfactual Fairness Evaluation of Machine Learning Models on Educational Datasets
by: Kim, Woojin, et al.
Published: (2025)
by: Kim, Woojin, et al.
Published: (2025)
Debiasing Diffusion Model: Enhancing Fairness through Latent Representation Learning in Stable Diffusion Model
by: Huang, Lin-Chun, et al.
Published: (2025)
by: Huang, Lin-Chun, et al.
Published: (2025)
Distribution-Free Fair Federated Learning with Small Samples
by: Yin, Qichuan, et al.
Published: (2024)
by: Yin, Qichuan, et al.
Published: (2024)
Long-Term Fair Decision Making through Deep Generative Models
by: Hu, Yaowei, et al.
Published: (2024)
by: Hu, Yaowei, et al.
Published: (2024)
FairSIN: Achieving Fairness in Graph Neural Networks through Sensitive Information Neutralization
by: Yang, Cheng, et al.
Published: (2024)
by: Yang, Cheng, et al.
Published: (2024)
A Sequentially Fair Mechanism for Multiple Sensitive Attributes
by: Hu, François, et al.
Published: (2023)
by: Hu, François, et al.
Published: (2023)
Achieving Fairness Across Local and Global Models in Federated Learning
by: Makhija, Disha, et al.
Published: (2024)
by: Makhija, Disha, et al.
Published: (2024)
Physics-Guided Fair Graph Sampling for Water Temperature Prediction in River Networks
by: He, Erhu, et al.
Published: (2024)
by: He, Erhu, et al.
Published: (2024)
FairPFN: A Tabular Foundation Model for Causal Fairness
by: Robertson, Jake, et al.
Published: (2025)
by: Robertson, Jake, et al.
Published: (2025)
Boosting Fair Classifier Generalization through Adaptive Priority Reweighing
by: Hu, Zhihao, et al.
Published: (2023)
by: Hu, Zhihao, et al.
Published: (2023)
Data Augmentation via Diffusion Model to Enhance AI Fairness
by: Blow, Christina Hastings, et al.
Published: (2024)
by: Blow, Christina Hastings, et al.
Published: (2024)
FairSample: Training Fair and Accurate Graph Convolutional Neural Networks Efficiently
by: Cong, Zicun, et al.
Published: (2024)
by: Cong, Zicun, et al.
Published: (2024)
How Robust is your Fair Model? Exploring the Robustness of Diverse Fairness Strategies
by: Small, Edward, et al.
Published: (2022)
by: Small, Edward, et al.
Published: (2022)
Evaluating Large Language Models for Fair and Reliable Organ Allocation
by: Kim, Brian Hyeongseok, et al.
Published: (2025)
by: Kim, Brian Hyeongseok, et al.
Published: (2025)
Exploring Equality: An Investigation into Custom Loss Functions for Fairness Definitions
by: Lee, Gordon, et al.
Published: (2025)
by: Lee, Gordon, et al.
Published: (2025)
Enhancing Fairness through Reweighting: A Path to Attain the Sufficiency Rule
by: Zhao, Xuan, et al.
Published: (2024)
by: Zhao, Xuan, et al.
Published: (2024)
On Prediction-Modelers and Decision-Makers: Why Fairness Requires More Than a Fair Prediction Model
by: Scantamburlo, Teresa, et al.
Published: (2023)
by: Scantamburlo, Teresa, et al.
Published: (2023)
FairPair: A Robust Evaluation of Biases in Language Models through Paired Perturbations
by: Dwivedi-Yu, Jane, et al.
Published: (2024)
by: Dwivedi-Yu, Jane, et al.
Published: (2024)
FairHome: A Fair Housing and Fair Lending Dataset
by: Bagalkotkar, Anusha, et al.
Published: (2024)
by: Bagalkotkar, Anusha, et al.
Published: (2024)
Tracing Mathematical Proficiency Through Problem-Solving Processes
by: Park, Jungyang, et al.
Published: (2025)
by: Park, Jungyang, et al.
Published: (2025)
Friends in Unexpected Places: Enhancing Local Fairness in Federated Learning through Clustering
by: Yang, Yifan, et al.
Published: (2024)
by: Yang, Yifan, et al.
Published: (2024)
FairWire: Fair Graph Generation
by: Kose, O. Deniz, et al.
Published: (2024)
by: Kose, O. Deniz, et al.
Published: (2024)
Auditing LLMs for Algorithmic Fairness in Casenote-Augmented Tabular Prediction
by: Lee, Xiao Qi, et al.
Published: (2026)
by: Lee, Xiao Qi, et al.
Published: (2026)
Positive-Sum Fairness: Leveraging Demographic Attributes to Achieve Fair AI Outcomes Without Sacrificing Group Gains
by: Belhadj, Samia, et al.
Published: (2024)
by: Belhadj, Samia, et al.
Published: (2024)
FairGT: A Fairness-aware Graph Transformer
by: Luo, Renqiang, et al.
Published: (2024)
by: Luo, Renqiang, et al.
Published: (2024)
What is Fair? Defining Fairness in Machine Learning for Health
by: Gao, Jianhui, et al.
Published: (2024)
by: Gao, Jianhui, et al.
Published: (2024)
Assessing Predictive Models for Fairness Based on Movement Patterns
by: Lettich, Francesco, et al.
Published: (2026)
by: Lettich, Francesco, et al.
Published: (2026)
Enhancing Multi-Attribute Fairness in Healthcare Predictive Modeling
by: Wang, Xiaoyang, et al.
Published: (2025)
by: Wang, Xiaoyang, et al.
Published: (2025)
Finetuning Text-to-Image Diffusion Models for Fairness
by: Shen, Xudong, et al.
Published: (2023)
by: Shen, Xudong, et al.
Published: (2023)
AdapFair: Ensuring Adaptive Fairness for Machine Learning Operations
by: Huang, Yinghui, et al.
Published: (2024)
by: Huang, Yinghui, et al.
Published: (2024)
Similar Items
-
Stability Analysis of Sharpness-Aware Minimization
by: Kim, Hoki, et al.
Published: (2023) -
BayesNAM: Leveraging Inconsistency for Reliable Explanations
by: Kim, Hoki, et al.
Published: (2024) -
Leveraging Programmatically Generated Synthetic Data for Differentially Private Diffusion Training
by: Choi, Yujin, et al.
Published: (2024) -
Are Self-Attentions Effective for Time Series Forecasting?
by: Kim, Dongbin, et al.
Published: (2024) -
Multi-Class Support Vector Machine with Differential Privacy
by: Park, Jinseong, et al.
Published: (2025)