Adversarial Robustness in Two-Stage Learning-to-Defer: Algorithms and Guarantees
Fuente:
arXiv
Saved in:
| Main Authors: | Montreuil, Yannis, Carlier, Axel, Ng, Lai Xing, Ooi, Wei Tsang |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Adversarial Robustness in One-Stage Learning-to-Defer
by: Montreuil, Yannis, et al.
Published: (2025)
by: Montreuil, Yannis, et al.
Published: (2025)
One-Stage Top-$k$ Learning-to-Defer: Score-Based Surrogates with Theoretical Guarantees
by: Montreuil, Yannis, et al.
Published: (2025)
by: Montreuil, Yannis, et al.
Published: (2025)
Learning-to-Defer with Expert-Conditional Advice
by: Montreuil, Yannis, et al.
Published: (2026)
by: Montreuil, Yannis, et al.
Published: (2026)
A Two-Stage Learning-to-Defer Approach for Multi-Task Learning
by: Montreuil, Yannis, et al.
Published: (2024)
by: Montreuil, Yannis, et al.
Published: (2024)
Beyond Augmented-Action Surrogates for Multi-Expert Learning-to-Defer
by: Montreuil, Yannis, et al.
Published: (2026)
by: Montreuil, Yannis, et al.
Published: (2026)
Why Ask One When You Can Ask $k$? Learning-to-Defer to the Top-$k$ Experts
by: Montreuil, Yannis, et al.
Published: (2025)
by: Montreuil, Yannis, et al.
Published: (2025)
Optimal Query Allocation in Extractive QA with LLMs: A Learning-to-Defer Framework with Theoretical Guarantees
by: Montreuil, Yannis, et al.
Published: (2024)
by: Montreuil, Yannis, et al.
Published: (2024)
Learning-to-Defer in Non-Stationary Time Series via Switching State-Space Models
by: Montreuil, Yannis, et al.
Published: (2026)
by: Montreuil, Yannis, et al.
Published: (2026)
Online Learning-to-Defer with Varying Experts
by: Duy, Dang Hoang, et al.
Published: (2026)
by: Duy, Dang Hoang, et al.
Published: (2026)
Mastering Multiple-Expert Routing: Realizable $H$-Consistency and Strong Guarantees for Learning to Defer
by: Mao, Anqi, et al.
Published: (2025)
by: Mao, Anqi, et al.
Published: (2025)
When Flatness Does (Not) Guarantee Adversarial Robustness
by: Walter, Nils Philipp, et al.
Published: (2025)
by: Walter, Nils Philipp, et al.
Published: (2025)
Deferring Concept Bottleneck Models: Learning to Defer Interventions to Inaccurate Experts
by: Pugnana, Andrea, et al.
Published: (2025)
by: Pugnana, Andrea, et al.
Published: (2025)
FedRLHF: A Convergence-Guaranteed Federated Framework for Privacy-Preserving and Personalized RLHF
by: Fan, Flint Xiaofeng, et al.
Published: (2024)
by: Fan, Flint Xiaofeng, et al.
Published: (2024)
Learning to Partially Defer for Sequences
by: Rayan, Sahana, et al.
Published: (2025)
by: Rayan, Sahana, et al.
Published: (2025)
Algorithms for Adversarially Robust Deep Learning
by: Robey, Alexander
Published: (2025)
by: Robey, Alexander
Published: (2025)
Adversarial Robustness Guarantees for Quantum Classifiers
by: Dowling, Neil, et al.
Published: (2024)
by: Dowling, Neil, et al.
Published: (2024)
Principled Approaches for Learning to Defer with Multiple Experts
by: Mao, Anqi, et al.
Published: (2023)
by: Mao, Anqi, et al.
Published: (2023)
Enhanced Parcel Arrival Forecasting for Logistic Hubs: An Ensemble Deep Learning Approach
by: Pan, Xinyue, et al.
Published: (2026)
by: Pan, Xinyue, et al.
Published: (2026)
An Efficient Learning-Based Solver for Two-Stage DC Optimal Power Flow with Feasibility Guarantees
by: Zhang, Ling, et al.
Published: (2023)
by: Zhang, Ling, et al.
Published: (2023)
Towards Robust Learning to Optimize with Theoretical Guarantees
by: Song, Qingyu, et al.
Published: (2025)
by: Song, Qingyu, et al.
Published: (2025)
Learning to Defer: A Survey
by: Strong, Joshua, et al.
Published: (2025)
by: Strong, Joshua, et al.
Published: (2025)
Learning to Defer to a Population: A Meta-Learning Approach
by: Tailor, Dharmesh, et al.
Published: (2024)
by: Tailor, Dharmesh, et al.
Published: (2024)
Density-Ratio Losses for Post-Hoc Learning to Defer
by: Soen, Alexander, et al.
Published: (2026)
by: Soen, Alexander, et al.
Published: (2026)
Fatigue-Aware Learning to Defer via Constrained Optimisation
by: Zhang, Zheng, et al.
Published: (2026)
by: Zhang, Zheng, et al.
Published: (2026)
Learning to Defer for Causal Discovery with Imperfect Experts
by: Clivio, Oscar, et al.
Published: (2025)
by: Clivio, Oscar, et al.
Published: (2025)
Provably Efficient Off-Policy Adversarial Imitation Learning with Convergence Guarantees
by: Chen, Yilei, et al.
Published: (2024)
by: Chen, Yilei, et al.
Published: (2024)
Adv-SSL: Adversarial Self-Supervised Representation Learning with Theoretical Guarantees
by: Duan, Chenguang, et al.
Published: (2024)
by: Duan, Chenguang, et al.
Published: (2024)
Deep Learning for Two-Stage Robust Integer Optimization
by: Dumouchelle, Justin, et al.
Published: (2023)
by: Dumouchelle, Justin, et al.
Published: (2023)
Deferred is Better: A Framework for Multi-Granularity Deferred Interaction of Heterogeneous Features
by: Xu, Yi, et al.
Published: (2026)
by: Xu, Yi, et al.
Published: (2026)
Enhancing Adversarial Robustness with Conformal Prediction: A Framework for Guaranteed Model Reliability
by: Bao, Jie, et al.
Published: (2025)
by: Bao, Jie, et al.
Published: (2025)
Deep Learning Meets Queue-Reactive: A Framework for Realistic Limit Order Book Simulation
by: Bodor, Hamza, et al.
Published: (2025)
by: Bodor, Hamza, et al.
Published: (2025)
A Machine Learning Approach to Two-Stage Adaptive Robust Optimization
by: Bertsimas, Dimitris, et al.
Published: (2023)
by: Bertsimas, Dimitris, et al.
Published: (2023)
Learning Scenario Reduction for Two-Stage Robust Optimization with Discrete Uncertainty
by: Lin, Tianjue, et al.
Published: (2026)
by: Lin, Tianjue, et al.
Published: (2026)
Realizable $H$-Consistent and Bayes-Consistent Loss Functions for Learning to Defer
by: Mao, Anqi, et al.
Published: (2024)
by: Mao, Anqi, et al.
Published: (2024)
When More Experts Hurt: Underfitting in Multi-Expert Learning to Defer
by: Liu, Shuqi, et al.
Published: (2026)
by: Liu, Shuqi, et al.
Published: (2026)
Debiasing Reward Models by Representation Learning with Guarantees
by: Ng, Ignavier, et al.
Published: (2025)
by: Ng, Ignavier, et al.
Published: (2025)
Fair Representation Learning with Controllable High Confidence Guarantees via Adversarial Inference
by: Luo, Yuhong, et al.
Published: (2025)
by: Luo, Yuhong, et al.
Published: (2025)
Near-Optimal Second-Order Guarantees for Model-Based Adversarial Imitation Learning
by: Li, Shangzhe, et al.
Published: (2025)
by: Li, Shangzhe, et al.
Published: (2025)
Toward Robust Signed Graph Learning through Joint Input-Target Denoising
by: Wu, Junran, et al.
Published: (2025)
by: Wu, Junran, et al.
Published: (2025)
Ensuring Calibration Robustness in Split Conformal Prediction Under Adversarial Attacks
by: Qian, Xunlei, et al.
Published: (2025)
by: Qian, Xunlei, et al.
Published: (2025)
Similar Items
-
Adversarial Robustness in One-Stage Learning-to-Defer
by: Montreuil, Yannis, et al.
Published: (2025) -
One-Stage Top-$k$ Learning-to-Defer: Score-Based Surrogates with Theoretical Guarantees
by: Montreuil, Yannis, et al.
Published: (2025) -
Learning-to-Defer with Expert-Conditional Advice
by: Montreuil, Yannis, et al.
Published: (2026) -
A Two-Stage Learning-to-Defer Approach for Multi-Task Learning
by: Montreuil, Yannis, et al.
Published: (2024) -
Beyond Augmented-Action Surrogates for Multi-Expert Learning-to-Defer
by: Montreuil, Yannis, et al.
Published: (2026)