Image de couverture de livre

Rethinking and Recomputing the Value of Machine Learning Models

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Sayin, Burcu, Yang, Jie, Chen, Xinyue, Passerini, Andrea, Casati, Fabio
Format:	Preprint
Publié:	2022
Sujets:	Machine Learning Artificial Intelligence
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Learning To Guide Human Decision Makers With Vision-Language Models
par: Banerjee, Debodeep, et autres
Publié: (2024)

MedSyn: Enhancing Diagnostics with Human-AI Collaboration
par: Sayin, Burcu, et autres
Publié: (2025)

KV Packet: Recomputation-Free Context-Independent KV Caching for LLMs
par: Chen, Chuangtao, et autres
Publié: (2026)

Can LLMs Correct Physicians, Yet? Investigating Effective Interaction Methods in the Medical Domain
par: Sayin, Burcu, et autres
Publié: (2024)

MedGellan: LLM-Generated Medical Guidance to Support Physicians
par: Banerjee, Debodeep, et autres
Publié: (2025)

Probabilistic ML Verification via Weighted Model Integration
par: Morettin, Paolo, et autres
Publié: (2024)

Hybrid Decision Making via Conformal VLM-generated Guidance
par: Banerjee, Debodeep, et autres
Publié: (2026)

Rethinking GNNs and Missing Features: Challenges, Evaluation and a Robust Solution
par: Ferrini, Francesco, et autres
Publié: (2026)

Concise and Logically Consistent Conformal Sets for Neuro-Symbolic Concept-Based Models
par: Bortolotti, Samuele, et autres
Publié: (2026)

Boosting Relational Deep Learning with Pretrained Tabular Models
par: Lachi, Veronica, et autres
Publié: (2025)

Shortcuts and Identifiability in Concept-based Models from a Neuro-Symbolic Lens
par: Bortolotti, Samuele, et autres
Publié: (2025)

Actionable Real-Time Modeling of Surgical Team Dynamics via Time-Expanded Interaction Graphs
par: De Luca, Vincenzo Marco, et autres
Publié: (2026)

Reconsidering Faithfulness in Regular, Self-Explainable and Domain Invariant GNNs
par: Azzolin, Steve, et autres
Publié: (2024)

Divide et Calibra: Multiclass Local Calibration via Vector Quantization
par: Barbera, Cesare, et autres
Publié: (2026)

Multiclass Local Calibration with the Jensen-Shannon Distance
par: Barbera, Cesare, et autres
Publié: (2025)

Beyond Shapley Values: Cooperative Games for the Interpretation of Machine Learning Models
par: Idrissi, Marouane Il, et autres
Publié: (2025)

Rethinking KL Regularization in RLHF: From Value Estimation to Gradient Optimization
par: Liu, Kezhao, et autres
Publié: (2025)

BEARS Make Neuro-Symbolic Models Aware of their Reasoning Shortcuts
par: Marconato, Emanuele, et autres
Publié: (2024)

Rethinking Key-Value Cache Compression Techniques for Large Language Model Serving
par: Gao, Wei, et autres
Publié: (2025)

GNN Explanations that do not Explain and How to find Them
par: Azzolin, Steve, et autres
Publié: (2026)

xAI-Drop: Don't Use What You Cannot Explain
par: De Luca, Vincenzo Marco, et autres
Publié: (2024)

Simple Path Structural Encoding for Graph Transformers
par: Airale, Louis, et autres
Publié: (2025)

LayerPipe2: Multistage Pipelining and Weight Recompute via Improved Exponential Moving Average for Training Neural Networks
par: Unnikrishnan, Nanda K., et autres
Publié: (2025)

Meta Additive Model: Interpretable Sparse Learning With Auto Weighting
par: Zhang, Xuelin, et autres
Publié: (2026)

Personalized Algorithmic Recourse with Preference Elicitation
par: De Toni, Giovanni, et autres
Publié: (2022)

Don't stop me now: Rethinking Validation Criteria for Model Parameter Selection
par: Apicella, Andrea, et autres
Publié: (2026)

Decorrelated Soft Actor-Critic for Efficient Deep Reinforcement Learning
par: Küçükoğlu, Burcu, et autres
Publié: (2025)

Bridging Theory and Practice in Link Representation with Graph Neural Networks
par: Lachi, Veronica, et autres
Publié: (2025)

Learning Human-like Representations to Enable Learning Human Values
par: Wynn, Andrea, et autres
Publié: (2023)

Rethinking Dimensional Rationale in Graph Contrastive Learning from Causal Perspective
par: Ji, Qirui, et autres
Publié: (2023)

VL-Rethinker: Incentivizing Self-Reflection of Vision-Language Models with Reinforcement Learning
par: Wang, Haozhe, et autres
Publié: (2025)

Subjectivity in Unsupervised Machine Learning Model Selection
par: Chen, Wanyi, et autres
Publié: (2023)

Innate-Values-driven Reinforcement Learning based Cognitive Modeling
par: Yang, Qin
Publié: (2024)

Rethinking the Role of Temperature in Large Language Model Distillation
par: Luong, Hoang-Chau, et autres
Publié: (2026)

Learning to Explore with Parameter-Space Noise: A Deep Dive into Parameter-Space Noise for Reinforcement Learning with Verifiable Rewards
par: Bai, Bizhe, et autres
Publié: (2026)

Explaining the Explainers in Graph Neural Networks: a Comparative Study
par: Longa, Antonio, et autres
Publié: (2022)

VRPO: Rethinking Value Modeling for Robust RL Training under Noisy Supervision
par: Zhu, Dingwei, et autres
Publié: (2025)

Losing is for Cherishing: Data Valuation Based on Machine Unlearning and Shapley Value
par: Ma, Le, et autres
Publié: (2025)

Hyperdimensional Probe: Decoding LLM Representations via Vector Symbolic Architectures
par: Bronzini, Marco, et autres
Publié: (2025)

Rethinking LoRA for Privacy-Preserving Federated Learning in Large Models
par: Liu, Jin, et autres
Publié: (2026)