Cover Image

A Unifying Post-Processing Framework for Multi-Objective Learn-to-Defer Problems

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Charusaie, Mohammad-Amin, Samadi, Samira
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

A Causal Framework for Evaluating Deferring Systems
by: Palomba, Filippo, et al.
Published: (2024)

A Unified Framework for Gradient Aggregation in Multi-Objective Optimization
by: Hu, Zeou, et al.
Published: (2026)

Learning to Defer for Causal Discovery with Imperfect Experts
by: Clivio, Oscar, et al.
Published: (2025)

Interactive Hyperparameter Optimization in Multi-Objective Problems via Preference Learning
by: Giovanelli, Joseph, et al.
Published: (2023)

Safe and Balanced: A Framework for Constrained Multi-Objective Reinforcement Learning
by: Gu, Shangding, et al.
Published: (2024)

An Offline Adaptation Framework for Constrained Multi-Objective Reinforcement Learning
by: Lin, Qian, et al.
Published: (2024)

Learning to Defer: A Survey
by: Strong, Joshua, et al.
Published: (2025)

Cost-Sensitive Learning to Defer to Multiple Experts with Workload Constraints
by: Alves, Jean V., et al.
Published: (2024)

Hybrid Learners Do Not Forget: A Brain-Inspired Neuro-Symbolic Approach to Continual Learning
by: Banayeeanzade, Amin, et al.
Published: (2025)

Projection Optimization: A General Framework for Multi-Objective and Multi-Group RLHF
by: Xiong, Nuoya, et al.
Published: (2025)

Optimistic Reinforcement Learning with Quantile Objectives
by: Alipour-Vaezi, Mohammad, et al.
Published: (2025)

Debate as Reward: A Multi-Agent Reward System for Scientific Ideation via RL Post-Training
by: Salimi, Moein, et al.
Published: (2026)

Multi-Objective Multi-Fidelity Bayesian Optimization with Causal Priors
by: Hossen, Md Abir, et al.
Published: (2026)

A Post-Processing-Based Fair Federated Learning Framework
by: Zhou, Yi, et al.
Published: (2025)

When Policies Cannot Be Retrained: A Unified Closed-Form View of Post-Training Steering in Offline Reinforcement Learning
by: Hossain, Elias, et al.
Published: (2026)

Demonstration Guided Multi-Objective Reinforcement Learning
by: Lu, Junlin, et al.
Published: (2024)

Multi-Objective Reinforcement Learning for Water Management
by: Osika, Zuzanna, et al.
Published: (2025)

Harmonizing Multi-Objective LLM Unlearning via Unified Domain Representation and Bidirectional Logit Distillation
by: Zhong, Yisheng, et al.
Published: (2026)

TREX: Trajectory Explanations for Multi-Objective Reinforcement Learning
by: Rajapakse, Dilina, et al.
Published: (2026)

Divide and Learn: Multi-Objective Combinatorial Optimization at Scale
by: Singh, Esha, et al.
Published: (2026)

Interpretability by Design for Efficient Multi-Objective Reinforcement Learning
by: Xia, Qiyue, et al.
Published: (2025)

DNN Memory Footprint Reduction via Post-Training Intra-Layer Multi-Precision Quantization
by: Ghavami, Behnam, et al.
Published: (2024)

A Unifying Framework for Learning Argumentation Semantics
by: Mileva, Zlatina, et al.
Published: (2023)

From Solving to Verifying: A Unified Objective for Robust Reasoning in LLMs
by: Wang, Xiaoxuan, et al.
Published: (2025)

SAFE-RL: Saliency-Aware Counterfactual Explainer for Deep Reinforcement Learning Policies
by: Samadi, Amir, et al.
Published: (2024)

A Meta-Learning Approach for Multi-Objective Reinforcement Learning in Sustainable Home Environments
by: Lu, Junlin, et al.
Published: (2024)

Flexible Swarm Learning May Outpace Foundation Models in Essential Tasks
by: Samadi, Moein E., et al.
Published: (2025)

In Search for Architectures and Loss Functions in Multi-Objective Reinforcement Learning
by: Terekhov, Mikhail, et al.
Published: (2024)

Multi-Objective Loss Balancing for Physics-Informed Deep Learning
by: Bischof, Rafael, et al.
Published: (2021)

CAFP: A Post-Processing Framework for Group Fairness via Counterfactual Model Averaging
by: Arévalo, Irina, et al.
Published: (2026)

Mirror Learning: A Unifying Framework of Policy Optimisation
by: Kuba, Jakub Grudzien, et al.
Published: (2022)

A Unified Framework for Heterogeneous Semi-supervised Learning
by: Heidari, Marzi, et al.
Published: (2025)

A Unified Invariant Learning Framework for Graph Classification
by: Sui, Yongduo, et al.
Published: (2025)

Multi-Objective Learning for Diffusion Models: A Statistical Theory under Semi-Supervised Learning
by: Cheng, Ziheng, et al.
Published: (2026)

In-Context Multi-Objective Optimization
by: Zhang, Xinyu, et al.
Published: (2025)

Unlearn to Relearn Backdoors: Deferred Backdoor Functionality Attacks on Deep Learning Models
by: Shin, Jeongjin, et al.
Published: (2024)

A New Approach to Backtracking Counterfactual Explanations: A Unified Causal Framework for Efficient Model Interpretability
by: Fatemi, Pouria, et al.
Published: (2025)

RLFactory: A Plug-and-Play Reinforcement Learning Post-Training Framework for LLM Multi-Turn Tool-Use
by: Chai, Jiajun, et al.
Published: (2025)

Navigating Trade-offs: Policy Summarization for Multi-Objective Reinforcement Learning
by: Osika, Zuzanna, et al.
Published: (2024)

Multi-Objective Neural Architecture Search by Learning Search Space Partitions
by: Zhao, Yiyang, et al.
Published: (2024)