Image de couverture de livre

Class-attribute Priors: Adapting Optimization to Heterogeneity and Fairness Objective

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Zhang, Xuechen, Li, Mingchen, Chen, Jiasi, Thrampoulidis, Christos, Oymak, Samet
Format:	Preprint
Publié:	2024
Sujets:	Machine Learning Computers and Society
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Selective Attention: Enhancing Transformer through Principled Context Control
par: Zhang, Xuechen, et autres
Publié: (2024)

On the Power of Convolution Augmented Transformer
par: Li, Mingchen, et autres
Publié: (2024)

VSPO: Vector-Steered Policy Optimization for Behavioral Control
par: Zhang, Xuechen, et autres
Publié: (2026)

SmartChunk Retrieval: Query-Aware Chunk Compression with Planning for Efficient Document RAG
par: Zhang, Xuechen, et autres
Publié: (2025)

Transformers as Support Vector Machines
par: Tarzanagh, Davoud Ataee, et autres
Publié: (2023)

BREAD: Branched Rollouts from Expert Anchors Bridge SFT & RL for Reasoning
par: Zhang, Xuechen, et autres
Publié: (2025)

LLM-Assisted Content Conditional Debiasing for Fair Text Embedding
par: Deng, Wenlong, et autres
Publié: (2024)

Making Small Language Models Efficient Reasoners: Intervention, Supervision, Reinforcement
par: Zhang, Xuechen, et autres
Publié: (2025)

Efficient Contextual LLM Cascades through Budget-Constrained Policy Learning
par: Zhang, Xuechen, et autres
Publié: (2024)

Implicit Optimization Bias of Next-Token Prediction in Linear Models
par: Thrampoulidis, Christos
Publié: (2024)

Towards Harmless Rawlsian Fairness Regardless of Demographic Prior
par: Wang, Xuanqian, et autres
Publié: (2024)

FairBranch: Mitigating Bias Transfer in Fair Multi-task Learning
par: Roy, Arjun, et autres
Publié: (2023)

The Fairness-Quality Trade-off in Clustering
par: Hakim, Rashida, et autres
Publié: (2024)

FairMT: Fairness for Heterogeneous Multi-Task Learning
par: Hu, Guanyu, et autres
Publié: (2025)

Evolutionary Multi-Task Optimization for LLM-Guided Program Discovery
par: Gozeten, Halil Alperen, et autres
Publié: (2026)

Social Choice for Heterogeneous Fairness in Recommendation
par: Aird, Amanda, et autres
Publié: (2024)

Latent Chain-of-Thought Improves Structured-Data Transformers
par: Dudley, Carson, et autres
Publié: (2026)

Adapting Static Fairness to Sequential Decision-Making: Bias Mitigation Strategies towards Equal Long-term Benefit Rate
par: Xu, Yuancheng, et autres
Publié: (2023)

Navigating Towards Fairness with Data Selection
par: Zhang, Yixuan, et autres
Publié: (2024)

Fairness-aware Federated Minimax Optimization with Convergence Guarantee
par: Dunda, Gerry Windiarto Mohamad, et autres
Publié: (2023)

BoostFGL: Boosting Fairness in Federated Graph Learning
par: Chen, Zekai, et autres
Publié: (2026)

FairGT: A Fairness-aware Graph Transformer
par: Luo, Renqiang, et autres
Publié: (2024)

Fairness Risks for Group-conditionally Missing Demographics
par: Jiang, Kaiqi, et autres
Publié: (2024)

Attention with Trained Embeddings Provably Selects Important Tokens
par: Wu, Diyuan, et autres
Publié: (2025)

FairHome: A Fair Housing and Fair Lending Dataset
par: Bagalkotkar, Anusha, et autres
Publié: (2024)

Cognitive Structure Generation: From Educational Priors to Policy Optimization
par: Gu, Hengnian, et autres
Publié: (2025)

Fine-grained Analysis of In-context Linear Estimation: Data, Architecture, and Beyond
par: Li, Yingcong, et autres
Publié: (2024)

Toward Fair Graph Neural Networks Via Dual-Teacher Knowledge Distillation
par: Li, Chengyu, et autres
Publié: (2024)

FairWire: Fair Graph Generation
par: Kose, O. Deniz, et autres
Publié: (2024)

Fair Graph Representation Learning via Sensitive Attribute Disentanglement
par: Zhu, Yuchang, et autres
Publié: (2024)

Rethinking Individual Fairness in Deepfake Detection
par: Hou, Aryana, et autres
Publié: (2025)

How Robust is your Fair Model? Exploring the Robustness of Diverse Fairness Strategies
par: Small, Edward, et autres
Publié: (2022)

Facts in Stats: Impacts of Pretraining Diversity on Language Model Generalization
par: Behnia, Tina, et autres
Publié: (2025)

Migrate Demographic Group For Fair GNNs
par: Hu, YanMing, et autres
Publié: (2023)

Unlocking the Potential of Prompt-Tuning in Bridging Generalized and Personalized Federated Learning
par: Deng, Wenlong, et autres
Publié: (2023)

Quantifying the Cross-sectoral Intersecting Discrepancies within Multiple Groups Using Latent Class Analysis Towards Fairness
par: Yuan, Yingfang, et autres
Publié: (2024)

What is Fair? Defining Fairness in Machine Learning for Health
par: Gao, Jianhui, et autres
Publié: (2024)

Integrating Fairness and Model Pruning Through Bi-level Optimization
par: Dai, Yucong, et autres
Publié: (2023)

FairRAG: Fair Human Generation via Fair Retrieval Augmentation
par: Shrestha, Robik, et autres
Publié: (2024)

Test-Time Training Provably Improves Transformers as In-context Learners
par: Gozeten, Halil Alperen, et autres
Publié: (2025)