Saved in:
| Main Authors: | Liang, Zhangyong, Zhang, Ji, Wang, Xin, Zhang, Pengfei, Li, Zhao |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2404.19557 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Error Estimate and Convergence Analysis for Data Valuation
by: Liang, Zhangyong, et al.
Published: (2025)
by: Liang, Zhangyong, et al.
Published: (2025)
Manifold-Orthogonal Dual-spectrum Extrapolation for Parameterized Physics-Informed Neural Networks
by: Liang, Zhangyong, et al.
Published: (2026)
by: Liang, Zhangyong, et al.
Published: (2026)
Stochastic-Dimension Frozen Sampled Neural Network for High-Dimensional Gross-Pitaevskii Equations on Unbounded Domains
by: Liang, Zhangyong
Published: (2026)
by: Liang, Zhangyong
Published: (2026)
Stochastic Dimension Implicit Functional Projections for Exact Integral Conservation in High-Dimensional PINNs
by: Liang, Zhangyong
Published: (2026)
by: Liang, Zhangyong
Published: (2026)
Hybrid Iterative Neural Low-Regularity Integrator for Nonlinear Dispersive Equations
by: Liang, Zhangyong
Published: (2026)
by: Liang, Zhangyong
Published: (2026)
Disentangled Latent Dynamics Manifold Fusion for Solving Parameterized PDEs
by: Liang, Zhangyong
Published: (2026)
by: Liang, Zhangyong
Published: (2026)
Stochastic Dimension-Free Zeroth-Order Estimator for High-Dimensional and High-Order PINNs
by: Liang, Zhangyong, et al.
Published: (2026)
by: Liang, Zhangyong, et al.
Published: (2026)
Conflict-Aware Harmonized Rotational Gradient for Multiscale Kinetic Regimes
by: Liang, Zhangyong
Published: (2026)
by: Liang, Zhangyong
Published: (2026)
Categorical Optimization with Bayesian Anchored Latent Trust Regions for Structural Design under High-Dimensional Uncertainty
by: Liang, Zhangyong, et al.
Published: (2026)
by: Liang, Zhangyong, et al.
Published: (2026)
Constitutive parameterized deep energy method for solid mechanics problems with random material parameters
by: Liang, Zhangyong, et al.
Published: (2026)
by: Liang, Zhangyong, et al.
Published: (2026)
Minimax Optimality in Contextual Dynamic Pricing with General Valuation Models
by: Gong, Xueping, et al.
Published: (2024)
by: Gong, Xueping, et al.
Published: (2024)
Fast-DataShapley: Neural Modeling for Training Data Valuation
by: Sun, Haifeng, et al.
Published: (2025)
by: Sun, Haifeng, et al.
Published: (2025)
Data Distribution Valuation
by: Xu, Xinyi, et al.
Published: (2024)
by: Xu, Xinyi, et al.
Published: (2024)
LossVal: Efficient Data Valuation for Neural Networks
by: Wibiral, Tim, et al.
Published: (2024)
by: Wibiral, Tim, et al.
Published: (2024)
Data Valuation and Detections in Federated Learning
by: Li, Wenqian, et al.
Published: (2023)
by: Li, Wenqian, et al.
Published: (2023)
Sketching the Readout of Large Language Models for Scalable Data Attribution and Valuation
by: Ran, Yide, et al.
Published: (2026)
by: Ran, Yide, et al.
Published: (2026)
Is Data Valuation Learnable and Interpretable?
by: Wu, Ou, et al.
Published: (2024)
by: Wu, Ou, et al.
Published: (2024)
Actively Learning Reinforcement Learning: A Stochastic Optimal Control Approach
by: Ramadan, Mohammad S., et al.
Published: (2023)
by: Ramadan, Mohammad S., et al.
Published: (2023)
Efficient Data Valuation Approximation in Federated Learning: A Sampling-based Approach
by: Wei, Shuyue, et al.
Published: (2025)
by: Wei, Shuyue, et al.
Published: (2025)
A Foundational Brain Dynamics Model via Stochastic Optimal Control
by: Park, Joonhyeong, et al.
Published: (2025)
by: Park, Joonhyeong, et al.
Published: (2025)
Losing is for Cherishing: Data Valuation Based on Machine Unlearning and Shapley Value
by: Ma, Le, et al.
Published: (2025)
by: Ma, Le, et al.
Published: (2025)
Efficient Training of Neural SDEs Using Stochastic Optimal Control
by: Daems, Rembert, et al.
Published: (2025)
by: Daems, Rembert, et al.
Published: (2025)
Convex Dataset Valuation for Post-Training
by: Zeng, Siqi, et al.
Published: (2026)
by: Zeng, Siqi, et al.
Published: (2026)
Efficient Banzhaf-Based Data Valuation for $k$-Nearest Neighbors Classification
by: Zhang, Guangyi, et al.
Published: (2026)
by: Zhang, Guangyi, et al.
Published: (2026)
Lightweight and Robust Federated Data Valuation
by: Tang, Guojun, et al.
Published: (2025)
by: Tang, Guojun, et al.
Published: (2025)
Algorithm-Relative Trajectory Valuation in Policy Gradient Control
by: Li, Shihao, et al.
Published: (2025)
by: Li, Shihao, et al.
Published: (2025)
A Guaranteed-Stable Neural Network Approach for Optimal Control of Nonlinear Systems
by: Li, Anran, et al.
Published: (2025)
by: Li, Anran, et al.
Published: (2025)
Adaptive Diffusion Guidance via Stochastic Optimal Control
by: Azangulov, Iskander, et al.
Published: (2025)
by: Azangulov, Iskander, et al.
Published: (2025)
Challenges in Enabling Private Data Valuation
by: Fu, Yiwei, et al.
Published: (2026)
by: Fu, Yiwei, et al.
Published: (2026)
MDNS: Masked Diffusion Neural Sampler via Stochastic Optimal Control
by: Zhu, Yuchen, et al.
Published: (2025)
by: Zhu, Yuchen, et al.
Published: (2025)
Private, Augmentation-Robust and Task-Agnostic Data Valuation Approach for Data Marketplace
by: Jahani-Nezhad, Tayyebeh, et al.
Published: (2024)
by: Jahani-Nezhad, Tayyebeh, et al.
Published: (2024)
Data Valuation with Gradient Similarity
by: Evans, Nathaniel J., et al.
Published: (2024)
by: Evans, Nathaniel J., et al.
Published: (2024)
SAVA: Scalable Learning-Agnostic Data Valuation
by: Kessler, Samuel, et al.
Published: (2024)
by: Kessler, Samuel, et al.
Published: (2024)
On the Usage of Gaussian Process for Efficient Data Valuation
by: Bénesse, Clément, et al.
Published: (2025)
by: Bénesse, Clément, et al.
Published: (2025)
KAIROS: Scalable Model-Agnostic Data Valuation
by: Zhu, Jiongli, et al.
Published: (2025)
by: Zhu, Jiongli, et al.
Published: (2025)
Out-of-Distribution Generalized Dynamic Graph Neural Network with Disentangled Intervention and Invariance Promotion
by: Zhang, Zeyang, et al.
Published: (2023)
by: Zhang, Zeyang, et al.
Published: (2023)
Beyond Models! Explainable Data Valuation and Metric Adaption for Recommendation
by: Jia, Renqi, et al.
Published: (2025)
by: Jia, Renqi, et al.
Published: (2025)
Local Shapley: Model-Induced Locality and Optimal Reuse in Data Valuation
by: Yang, Xuan, et al.
Published: (2026)
by: Yang, Xuan, et al.
Published: (2026)
Nearly Optimal Bayesian Inference for Structural Missingness
by: Liang, Chen, et al.
Published: (2026)
by: Liang, Chen, et al.
Published: (2026)
Data Valuation and Selection in a Federated Model Marketplace
by: Li, Wenqian, et al.
Published: (2025)
by: Li, Wenqian, et al.
Published: (2025)
Similar Items
-
Error Estimate and Convergence Analysis for Data Valuation
by: Liang, Zhangyong, et al.
Published: (2025) -
Manifold-Orthogonal Dual-spectrum Extrapolation for Parameterized Physics-Informed Neural Networks
by: Liang, Zhangyong, et al.
Published: (2026) -
Stochastic-Dimension Frozen Sampled Neural Network for High-Dimensional Gross-Pitaevskii Equations on Unbounded Domains
by: Liang, Zhangyong
Published: (2026) -
Stochastic Dimension Implicit Functional Projections for Exact Integral Conservation in High-Dimensional PINNs
by: Liang, Zhangyong
Published: (2026) -
Hybrid Iterative Neural Low-Regularity Integrator for Nonlinear Dispersive Equations
by: Liang, Zhangyong
Published: (2026)