End-to-End Learning for Fair Multiobjective Optimization Under Uncertainty
Fuente:
arXiv
Saved in:
| Main Authors: | Dinh, My H, Kotary, James, Fioretto, Ferdinando |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
End-to-End Optimization and Learning of Fair Court Schedules
by: Dinh, My H, et al.
Published: (2024)
by: Dinh, My H, et al.
Published: (2024)
Learning Fair Ranking Policies via Differentiable Optimization of Ordered Weighted Averages
by: Dinh, My H., et al.
Published: (2024)
by: Dinh, My H., et al.
Published: (2024)
Analyzing and Enhancing the Backward-Pass Convergence of Unrolled Optimization
by: Kotary, James, et al.
Published: (2023)
by: Kotary, James, et al.
Published: (2023)
Learning Constrained Optimization with Deep Augmented Lagrangian Methods
by: Kotary, James, et al.
Published: (2024)
by: Kotary, James, et al.
Published: (2024)
Decision-Focused Learning: Foundations, State of the Art, Benchmark and Future Opportunities
by: Mandi, Jayanta, et al.
Published: (2023)
by: Mandi, Jayanta, et al.
Published: (2023)
Decision Making with Differential Privacy under a Fairness Lens
by: Fioretto, Ferdinando, et al.
Published: (2021)
by: Fioretto, Ferdinando, et al.
Published: (2021)
On The Fairness Impacts of Hardware Selection in Machine Learning
by: Nelaturu, Sree Harsha, et al.
Published: (2023)
by: Nelaturu, Sree Harsha, et al.
Published: (2023)
NeuroFilter: Privacy Guardrails for Conversational LLM Agents
by: Das, Saswat, et al.
Published: (2026)
by: Das, Saswat, et al.
Published: (2026)
Metric Learning to Accelerate Convergence of Operator Splitting Methods for Differentiable Parametric Programming
by: King, Ethan, et al.
Published: (2024)
by: King, Ethan, et al.
Published: (2024)
Fairness Issues and Mitigations in (Differentially Private) Socio-Demographic Data Processes
by: Ko, Joonhyuk, et al.
Published: (2024)
by: Ko, Joonhyuk, et al.
Published: (2024)
Fairness-aware Multiobjective Evolutionary Learning
by: Zhang, Qingquan, et al.
Published: (2024)
by: Zhang, Qingquan, et al.
Published: (2024)
Discrete-Guided Diffusion for Scalable and Safe Multi-Robot Motion Planning
by: Liang, Jinhao, et al.
Published: (2025)
by: Liang, Jinhao, et al.
Published: (2025)
Simulation-Informed Diffusion for Decentralized Multi-robot Motion Planning
by: Liang, Jinhao, et al.
Published: (2026)
by: Liang, Jinhao, et al.
Published: (2026)
The Data Minimization Principle in Machine Learning
by: Ganesh, Prakhar, et al.
Published: (2024)
by: Ganesh, Prakhar, et al.
Published: (2024)
Optimal Allocation of Privacy Budget on Hierarchical Data Release
by: Ko, Joonhyuk, et al.
Published: (2025)
by: Ko, Joonhyuk, et al.
Published: (2025)
Beyond Jailbreaking: Auditing Contextual Privacy in LLM Agents
by: Das, Saswat, et al.
Published: (2025)
by: Das, Saswat, et al.
Published: (2025)
EndToEndML: An Open-Source End-to-End Pipeline for Machine Learning Applications
by: Pillai, Nisha, et al.
Published: (2024)
by: Pillai, Nisha, et al.
Published: (2024)
Constrained Synthesis with Projected Diffusion Models
by: Christopher, Jacob K, et al.
Published: (2024)
by: Christopher, Jacob K, et al.
Published: (2024)
Differential Privacy Overview and Fundamental Techniques
by: Fioretto, Ferdinando, et al.
Published: (2024)
by: Fioretto, Ferdinando, et al.
Published: (2024)
Simple Self-Conditioning Adaptation for Masked Diffusion Models
by: Cardei, Michael, et al.
Published: (2026)
by: Cardei, Michael, et al.
Published: (2026)
Learning Joint Models of Prediction and Optimization
by: Kotary, James, et al.
Published: (2024)
by: Kotary, James, et al.
Published: (2024)
Meta-Harness: End-to-End Optimization of Model Harnesses
by: Lee, Yoonho, et al.
Published: (2026)
by: Lee, Yoonho, et al.
Published: (2026)
Constraint-Aware Flow Matching: Decision Aligned End-to-End Training for Constrained Sampling
by: Christopher, Jacob K., et al.
Published: (2026)
by: Christopher, Jacob K., et al.
Published: (2026)
Differentially Private Data Release on Graphs: Inefficiencies and Unfairness
by: Fioretto, Ferdinando, et al.
Published: (2024)
by: Fioretto, Ferdinando, et al.
Published: (2024)
Constraint-Informed Active Learning for End-to-End ACOPF Optimization Proxies
by: Li, Miao, et al.
Published: (2025)
by: Li, Miao, et al.
Published: (2025)
ORCA: An End-to-End Interactive Copilot for Optimized Root Cause Analysis
by: Xuan, Phi Nguyen, et al.
Published: (2026)
by: Xuan, Phi Nguyen, et al.
Published: (2026)
An Open-source End-to-End Logic Optimization Framework for Large-scale Boolean Network with Reinforcement Learning
by: Li, Zhen, et al.
Published: (2024)
by: Li, Zhen, et al.
Published: (2024)
Bridging the Divide: End-to-End Sequence-Graph Learning
by: Chen, Yuen, et al.
Published: (2025)
by: Chen, Yuen, et al.
Published: (2025)
End-to-End Neuro-Symbolic Reinforcement Learning with Textual Explanations
by: Luo, Lirui, et al.
Published: (2024)
by: Luo, Lirui, et al.
Published: (2024)
BPQP: A Differentiable Convex Optimization Framework for Efficient End-to-End Learning
by: Pan, Jianming, et al.
Published: (2024)
by: Pan, Jianming, et al.
Published: (2024)
Learning to Communicate: Toward End-to-End Optimization of Multi-Agent Language Systems
by: Yu, Ye, et al.
Published: (2026)
by: Yu, Ye, et al.
Published: (2026)
Search-Augmented Masked Diffusion Models for Constrained Generation
by: Ta, Huu Binh, et al.
Published: (2026)
by: Ta, Huu Binh, et al.
Published: (2026)
Neuro-Symbolic Generative Diffusion Models for Physically Grounded, Robust, and Safe Generation
by: Christopher, Jacob K., et al.
Published: (2025)
by: Christopher, Jacob K., et al.
Published: (2025)
End-to-End Evaluation for Low-Latency Simultaneous Speech Translation
by: Huber, Christian, et al.
Published: (2023)
by: Huber, Christian, et al.
Published: (2023)
Evolving-RL: End-to-End Optimization of Experience-Driven Self-Evolving Capability within Agents
by: Fan, Zhiyuan, et al.
Published: (2026)
by: Fan, Zhiyuan, et al.
Published: (2026)
Multi-Agent Path Finding in Continuous Spaces with Projected Diffusion Models
by: Liang, Jinhao, et al.
Published: (2024)
by: Liang, Jinhao, et al.
Published: (2024)
Simultaneous Multi-Robot Motion Planning with Projected Diffusion Models
by: Liang, Jinhao, et al.
Published: (2025)
by: Liang, Jinhao, et al.
Published: (2025)
A Modular End-to-End Multimodal Learning Method for Structured and Unstructured Data
by: Alessandro, Marco D, et al.
Published: (2024)
by: Alessandro, Marco D, et al.
Published: (2024)
EvaDrive: Evolutionary Adversarial Policy Optimization for End-to-End Autonomous Driving
by: Jiao, Siwen, et al.
Published: (2025)
by: Jiao, Siwen, et al.
Published: (2025)
Reinforced Reasoning for End-to-End Retrosynthetic Planning
by: Zuo, Chenyang, et al.
Published: (2026)
by: Zuo, Chenyang, et al.
Published: (2026)
Similar Items
-
End-to-End Optimization and Learning of Fair Court Schedules
by: Dinh, My H, et al.
Published: (2024) -
Learning Fair Ranking Policies via Differentiable Optimization of Ordered Weighted Averages
by: Dinh, My H., et al.
Published: (2024) -
Analyzing and Enhancing the Backward-Pass Convergence of Unrolled Optimization
by: Kotary, James, et al.
Published: (2023) -
Learning Constrained Optimization with Deep Augmented Lagrangian Methods
by: Kotary, James, et al.
Published: (2024) -
Decision-Focused Learning: Foundations, State of the Art, Benchmark and Future Opportunities
by: Mandi, Jayanta, et al.
Published: (2023)