Image de couverture de livre

The Role of Learning Algorithms in Collective Action

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Ben-Dov, Omri, Fawkes, Jake, Samadi, Samira, Sanyal, Amartya
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

Fairness for the People, by the People: Minority Collective Action
par: Ben-Dov, Omri, et autres
Publié: (2025)

The Fragility of Fairness: Causal Sensitivity Analysis for Fair Machine Learning
par: Fawkes, Jake, et autres
Publié: (2024)

Causal Fair Metric: Bridging Causality, Individual Fairness, and Adversarial Robustness
par: Ehyaei, Ahmad-Reza, et autres
Publié: (2023)

Algorithmic Collective Action with Two Collectives
par: Karan, Aditya, et autres
Publié: (2025)

$f$-Trajectory Balance: A Loss Family for Tuning GFlowNets, Generative Models, and LLMs with Off- and On-Policy Data
par: Fawkes, Jake, et autres
Publié: (2026)

Causal-EPIG: A Prediction-Oriented Active Learning Framework for CATE Estimation
par: Gao, Erdun, et autres
Publié: (2025)

Adaptive Symmetrization of the KL Divergence
par: Ben-Dov, Omri, et autres
Publié: (2025)

MachineLearnAthon: An Action-Oriented Machine Learning Didactic Concept
par: Tkáč, Michal, et autres
Publié: (2024)

Peer-induced Fairness: A Causal Approach for Algorithmic Fairness Auditing
par: Fang, Shiqi, et autres
Publié: (2024)

An Iterative Algorithm for Differentially Private $k$-PCA with Adaptive Noise
par: Düngler, Johanna, et autres
Publié: (2025)

"Model Cards for Model Reporting" in 2024: Reclassifying Category of Ethical Considerations in Terms of Trustworthiness and Risk Management
par: Kennedy-Mayo, DeBrae, et autres
Publié: (2024)

Statistical Guarantees in the Search for Less Discriminatory Algorithms
par: Hays, Chris, et autres
Publié: (2025)

Collective Counterfactual Explanations: Balancing Individual Goals and Collective Dynamics
par: Ehyaei, Ahmad-Reza, et autres
Publié: (2024)

Machine Learning Algorithms for Detecting Mental Stress in College Students
par: Singh, Ashutosh, et autres
Publié: (2024)

Quantum-Enhanced Forecasting for Deep Reinforcement Learning in Algorithmic Trading
par: Chen, Jun-Hao, et autres
Publié: (2025)

Automating Governing Knowledge Commons and Contextual Integrity (GKC-CI) Privacy Policy Annotations with Large Language Models
par: Chanenson, Jake, et autres
Publié: (2023)

Online Learning and Unlearning
par: Hu, Yaxi, et autres
Publié: (2025)

Algorithmic Fairness in Performative Policy Learning: Escaping the Impossibility of Group Fairness
par: Somerstep, Seamus, et autres
Publié: (2024)

FairPFN: A Tabular Foundation Model for Causal Fairness
par: Robertson, Jake, et autres
Publié: (2025)

Open Problems in Machine Unlearning for AI Safety
par: Barez, Fazl, et autres
Publié: (2025)

Fuck the Algorithm: Conceptual Issues in Algorithmic Bias
par: Stinson, Catherine
Publié: (2025)

Differentially Private Steering for Large Language Model Alignment
par: Goel, Anmol, et autres
Publié: (2025)

Language Generation with Replay: A Learning-Theoretic View of Model Collapse
par: Racca, Giorgio, et autres
Publié: (2026)

Development and Validation of a Machine Learning Algorithm for Clinical Wellness Visit Classification in Cats and Dogs
par: Szlosek, Donald, et autres
Publié: (2024)

Debias-CLR: A Contrastive Learning Based Debiasing Method for Algorithmic Fairness in Healthcare Applications
par: Agarwal, Ankita, et autres
Publié: (2024)

Investigating Role of Personal Factors in Shaping Responses to Active Shooter Incident using Machine Learning
par: Liu, Ruying, et autres
Publié: (2025)

Rethinking Fair Representation Learning for Performance-Sensitive Tasks
par: Jones, Charles, et autres
Publié: (2024)

A Primer on Causal and Statistical Dataset Biases for Fair and Robust Image Analysis
par: Jones, Charles, et autres
Publié: (2025)

Algorithmic Collective Action in Machine Learning
par: Hardt, Moritz, et autres
Publié: (2023)

Time Can Invalidate Algorithmic Recourse
par: De Toni, Giovanni, et autres
Publié: (2024)

Unprocessing Seven Years of Algorithmic Fairness
par: Cruz, André F., et autres
Publié: (2023)

RescueLens: LLM-Powered Triage and Action on Volunteer Feedback for Food Rescue
par: Raman, Naveen, et autres
Publié: (2025)

Use of Boosting Algorithms in Household-Level Poverty Measurement: A Machine Learning Approach to Predict and Classify Household Wealth Quintiles in the Philippines
par: Salvador, Erika Lynet
Publié: (2024)

What Constitutes a Less Discriminatory Algorithm?
par: Laufer, Benjamin, et autres
Publié: (2024)

Estimating Item Difficulty Using Large Language Models and Tree-Based Machine Learning Algorithms
par: Razavi, Pooya, et autres
Publié: (2025)

The Impact of Differential Feature Under-reporting on Algorithmic Fairness
par: Akpinar, Nil-Jana, et autres
Publié: (2024)

On the Growth of Mistakes in Differentially Private Online Learning: A Lower Bound Perspective
par: Dmitriev, Daniil, et autres
Publié: (2024)

FairPFN: Transformers Can do Counterfactual Fairness
par: Robertson, Jake, et autres
Publié: (2024)

From Individual Experience to Collective Evidence: A Reporting-Based Framework for Identifying Systemic Harms
par: Dai, Jessica, et autres
Publié: (2025)

Should We Attend More or Less? Modulating Attention for Fairness
par: Zayed, Abdelrahman, et autres
Publié: (2023)