:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Reid, Mirabel, Sühr, Tom, Vernade, Claire, Samadi, Samira
Format:	Preprint
Published:	2024
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2409.20489
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

A Dynamic Model of Performative Human-ML Collaboration: Theory and Empirical Evidence
by: Sühr, Tom, et al.
Published: (2024)

Challenging the Validity of Personality Tests for Large Language Models
by: Sühr, Tom, et al.
Published: (2023)

Budgeted Multiple-Expert Deferral
by: DeSalvo, Giulia, et al.
Published: (2025)

Prior-Dependent Allocations for Bayesian Fixed-Budget Best-Arm Identification in Structured Bandits
by: Nguyen, Nicolas, et al.
Published: (2024)

Position: Stop Evaluating AI with Human Tests, Develop Principled, AI-specific Tests instead
by: Sühr, Tom, et al.
Published: (2025)

Tight Sample Complexity Bounds for Entropic Best Policy Identification
by: Essakine, Amer, et al.
Published: (2026)

Partially Observable Reinforcement Learning with Memory Traces
by: Eberhard, Onno, et al.
Published: (2025)

Non-Stationary Lipschitz Bandits
by: Nguyen, Nicolas, et al.
Published: (2025)

Commit to the Bit: Reactive Reinforcement Learning Done Right
by: Eberhard, Onno, et al.
Published: (2026)

Improving Radiography Machine Learning Workflows via Metadata Management for Training Data Selection
by: Reid, Mirabel, et al.
Published: (2024)

Variational Bayes Portfolio Construction
by: Nguyen, Nicolas, et al.
Published: (2024)

A Pontryagin Perspective on Reinforcement Learning
by: Eberhard, Onno, et al.
Published: (2024)

Put CASH on Bandits: A Max K-Armed Problem for Automated Machine Learning
by: Balef, Amir Rezaei, et al.
Published: (2025)

A Unifying Post-Processing Framework for Multi-Objective Learn-to-Defer Problems
by: Charusaie, Mohammad-Amin, et al.
Published: (2024)

Split the Differences, Pool the Rest: Provably Efficient Multi-Objective Imitation
by: Sheebaelhamd, Ziyad, et al.
Published: (2026)

Quantization-Free Autoregressive Action Transformer
by: Sheebaelhamd, Ziyad, et al.
Published: (2025)

From Fragile to Certified: Wasserstein Audits of Group Fairness Under Distribution Shift
by: Ehyaei, Ahmad-Reza, et al.
Published: (2025)

Designing Ambiguity Sets for Distributionally Robust Optimization Using Structural Causal Optimal Transport
by: Ehyaei, Ahmad-Reza, et al.
Published: (2025)

Wasserstein Distributionally Robust Optimization Through the Lens of Structural Causal Models and Individual Fairness
by: Ehyaei, Ahmad-Reza, et al.
Published: (2025)

Collective Counterfactual Explanations: Balancing Individual Goals and Collective Dynamics
by: Ehyaei, Ahmad-Reza, et al.
Published: (2024)

Clustered KL-barycenter design for policy evaluation
by: Weissmann, Simon, et al.
Published: (2025)

Online Learning under Budget and ROI Constraints via Weak Adaptivity
by: Castiglioni, Matteo, et al.
Published: (2023)

Efficient Risk-sensitive Planning via Entropic Risk Measures
by: Marthe, Alexandre, et al.
Published: (2025)

Causal Fair Metric: Bridging Causality, Individual Fairness, and Adversarial Robustness
by: Ehyaei, Ahmad-Reza, et al.
Published: (2023)

Regression with Multi-Expert Deferral
by: Mao, Anqi, et al.
Published: (2024)

Optimized Deferral for Imbalanced Settings
by: Cortes, Corinna, et al.
Published: (2026)

Adaptive LLM Routing under Budget Constraints
by: Panda, Pranoy, et al.
Published: (2025)

Online Resource Allocation with Average Budget Constraints
by: Ao, Ruicheng, et al.
Published: (2024)

Optimal Policy Learning under Budget and Coverage Constraints
by: Cerulli, Giovanni
Published: (2026)

Safe Online Bid Optimization with Return on Investment and Budget Constraints
by: Castiglioni, Matteo, et al.
Published: (2022)

The Role of Learning Algorithms in Collective Action
by: Ben-Dov, Omri, et al.
Published: (2024)

Fairness for the People, by the People: Minority Collective Action
by: Ben-Dov, Omri, et al.
Published: (2025)

Cascaded Transfer: Learning Many Tasks under Budget Constraints
by: Campagne, Eloi, et al.
Published: (2026)

Identity-Free Deferral For Unseen Experts
by: Strong, Joshua, et al.
Published: (2025)

An Advanced Reinforcement Learning Framework for Online Scheduling of Deferrable Workloads in Cloud Computing
by: Dong, Hang, et al.
Published: (2024)

A New Benchmark for Online Learning with Budget-Balancing Constraints
by: Braverman, Mark, et al.
Published: (2025)

Fill-and-Spill: Deep Reinforcement Learning Policy Gradient Methods for Reservoir Operation Decision and Control
by: Tabas, Sadegh Sadeghi, et al.
Published: (2024)

When Does Confidence-Based Cascade Deferral Suffice?
by: Jitkrittum, Wittawat, et al.
Published: (2023)

Safe and Efficient Online Convex Optimization with Linear Budget Constraints and Partial Feedback
by: Liu, Shanqi, et al.
Published: (2024)

Joint Continual Learning of Local Language Models and Cloud Offloading Decisions with Budget Constraints
by: Chen, Evan, et al.
Published: (2026)