Cover Image

Differential Parity: Relative Fairness Between Two Sets of Decisions

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Yu, Zhe, Xi, Xiaoyin, Shetty, Pranam Prakash
Format:	Preprint
Published:	2021
Subjects:	Machine Learning 68T01
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Story Point Estimation Using Large Language Models
by: Shetty, Pranam Prakash, et al.
Published: (2026)

A Data-Driven Measure of Relative Uncertainty for Misclassification Detection
by: Dadalto, Eduardo, et al.
Published: (2023)

Physics-Informed Neural Networks and Neural Operators for Parametric PDEs
by: Zhang, Zhuo, et al.
Published: (2025)

The Selective G-Bispectrum and its Inversion: Applications to G-Invariant Networks
by: Mataigne, Simon, et al.
Published: (2024)

Differentially Private Prototypes for Imbalanced Transfer Learning
by: Wahdany, Dariush, et al.
Published: (2024)

A Human-In-The-Loop Approach for Improving Fairness in Predictive Business Process Monitoring
by: Käppel, Martin, et al.
Published: (2025)

AI-based modular warning machine for risk identification in proximity healthcare
by: Razzetta, Chiara, et al.
Published: (2025)

Strategic inputs: feature selection from game-theoretic perspective
by: Zhao, Chi, et al.
Published: (2025)

Evaluating AI Grading on Real-World Handwritten College Mathematics: A Large-Scale Study Toward a Benchmark
by: Yu, Zhiqi, et al.
Published: (2026)

Unveiling Group-Specific Distributed Concept Drift: A Fairness Imperative in Federated Learning
by: Salazar, Teresa, et al.
Published: (2024)

Freeze, Diffuse, Decode: Geometry-Aware Adaptation of Pretrained Transformer Embeddings for Antimicrobial Peptide Design
by: Gawade, Pankhil, et al.
Published: (2025)

ReMIA: a Powerful and Efficient Alternative to Membership Inference Attacks against Synthetic Data Generators
by: Scassola, Davide, et al.
Published: (2026)

Intrinsic Rewards for Exploration without Harm from Observational Noise: A Simulation Study Based on the Free Energy Principle
by: Tinker, Theodore Jerome, et al.
Published: (2024)

On the Optimal Memorization Capacity of Transformers
by: Kajitsuka, Tokio, et al.
Published: (2024)

Representation Integrity in Temporal Graph Learning Methods
by: Kooshafar, Elahe
Published: (2025)

Online Decision Making with Generative Action Sets
by: Xu, Jianyu, et al.
Published: (2025)

Modeling Membrane Degradation in PEM Electrolyzers with Physics-Informed Neural Networks
by: Polo-Molina, Alejandro, et al.
Published: (2025)

A theoretical basis for model collapse in recursive training
by: Borkar, Vivek Shripad
Published: (2025)

Optimal Bound for PCA with Outliers using Higher-Degree Voronoi Diagrams
by: Hashemian, Sajjad, et al.
Published: (2024)

Auditable Homomorphic-based Decentralized Collaborative AI with Attribute-based Differential Privacy
by: Yeh, Lo-Yao, et al.
Published: (2024)

Learning to Control the Smoothness of Graph Convolutional Network Features
by: Wang, Shih-Hsin, et al.
Published: (2024)

Tape: A Cellular Automata Benchmark for Evaluating Rule-Shift Generalization in Reinforcement Learning
by: Pan, Enze
Published: (2026)

seqme: a Python library for evaluating biological sequence design
by: Møller-Larsen, Rasmus, et al.
Published: (2025)

The Llama 4 Herd: Architecture, Training, Evaluation, and Deployment Notes
by: arXiv, Redacted by
Published: (2026)

Activity Detection for Massive Connectivity in Cell-free Networks with Unknown Large-scale Fading, Channel Statistics, Noise Variance, and Activity Probability: A Bayesian Approach
by: Zhang, Hao, et al.
Published: (2024)

RASP-Tuner: Retrieval-Augmented Soft Prompts for Context-Aware Black-Box Optimization in Non-Stationary Environments
by: Pan, Enze
Published: (2026)

A Theoretical Analysis of Soft-Label vs Hard-Label Training in Neural Networks
by: Mandal, Saptarshi, et al.
Published: (2024)

Learning from Similarity-Confidence and Confidence-Difference
by: Tate, Tomoya, et al.
Published: (2025)

Stabilizing Machine Learning for Reproducible and Explainable Results: A Novel Validation Approach to Subject-Specific Insights
by: Vos, Gideon, et al.
Published: (2024)

Learning from Hard Labels with Additional Supervision on Non-Hard-Labeled Classes
by: Sugiyama, Kosuke, et al.
Published: (2025)

Learning from Complementary Features
by: Sugiyama, Kosuke, et al.
Published: (2024)

Predictors of disease outbreaks at continentalscale in the African region: Insights and predictions with geospatial artificial intelligence using earth observations and routine disease surveillance data
by: Pezanowski, Scott, et al.
Published: (2024)

Fast, close, non-singular and property-preserving approximations of entropic measures
by: Horenko, Illia, et al.
Published: (2025)

FST.ai 2.0: An Explainable AI Ecosystem for Fair, Fast, and Inclusive Decision-Making in Olympic and Paralympic Taekwondo
by: Shariatmadar, Keivan, et al.
Published: (2025)

FairReweighing: Density Estimation-Based Reweighing Framework for Improving Separation in Fair Regression
by: Xi, Xiaoyin, et al.
Published: (2025)

Sequence Transferability and Task Order Selection in Continual Learning
by: Nguyen, Thinh, et al.
Published: (2025)

Frequency Principle: Fourier Analysis Sheds Light on Deep Neural Networks
by: Xu, Zhi-Qin John, et al.
Published: (2019)

Balanced Group Convolution: An Improved Group Convolution Based on Approximability Estimates
by: Lee, Youngkyu, et al.
Published: (2023)

Semantic Needles in Document Haystacks: Sensitivity Testing of LLM-as-a-Judge Similarity Scoring
by: Aksoy, Sinan G., et al.
Published: (2026)

Lecture notes on high-dimensional data
by: Wegner, Sven-Ake
Published: (2021)