Optimization on black-box function by parameter-shift rule
Fuente:
arXiv
Saved in:
| Main Author: | Hai, Vu Tuan |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Towards black-box parameter estimation
by: Lenzi, Amanda, et al.
Published: (2023)
by: Lenzi, Amanda, et al.
Published: (2023)
Time-Aware Latent Space Bayesian Optimization
by: Vu, Tuan A., et al.
Published: (2026)
by: Vu, Tuan A., et al.
Published: (2026)
Towards consistency of rule-based explainer and black box model -- fusion of rule induction and XAI-based feature importance
by: Kozielski, Michał, et al.
Published: (2024)
by: Kozielski, Michał, et al.
Published: (2024)
Gradients of unitary optical neural networks using parameter-shift rule
by: Jiang, Jinzhe, et al.
Published: (2025)
by: Jiang, Jinzhe, et al.
Published: (2025)
Investigating Bayesian optimization for expensive-to-evaluate black box functions: Application in fluid dynamics
by: Diessner, Mike, et al.
Published: (2022)
by: Diessner, Mike, et al.
Published: (2022)
Achieving interpretable machine learning by functional decomposition of black-box models into explainable predictor effects
by: Köhler, David, et al.
Published: (2024)
by: Köhler, David, et al.
Published: (2024)
Wild refitting for black box prediction
by: Wainwright, Martin J.
Published: (2025)
by: Wainwright, Martin J.
Published: (2025)
Joint control variate for faster black-box variational inference
by: Wang, Xi, et al.
Published: (2022)
by: Wang, Xi, et al.
Published: (2022)
Sample complexity of data-driven tuning of model hyperparameters in neural networks with structured parameter-dependent dual function
by: Balcan, Maria-Florina, et al.
Published: (2025)
by: Balcan, Maria-Florina, et al.
Published: (2025)
Stabilizing black-box model selection with the inflated argmax
by: Adrian, Melissa, et al.
Published: (2024)
by: Adrian, Melissa, et al.
Published: (2024)
Opening the AI black box: program synthesis via mechanistic interpretability
by: Michaud, Eric J., et al.
Published: (2024)
by: Michaud, Eric J., et al.
Published: (2024)
Personalizing black-box models for nonparametric regression with minimax optimality
by: Li, Sai, et al.
Published: (2026)
by: Li, Sai, et al.
Published: (2026)
Visualizing token importance for black-box language models
by: Rauba, Paulius, et al.
Published: (2025)
by: Rauba, Paulius, et al.
Published: (2025)
AED: An black-box NLP classifier model attacker
by: Liu, Yueyang, et al.
Published: (2021)
by: Liu, Yueyang, et al.
Published: (2021)
Concentration bounds on response-based vector embeddings of black-box generative models
by: Acharyya, Aranyak, et al.
Published: (2025)
by: Acharyya, Aranyak, et al.
Published: (2025)
Black-box optimization of noisy functions with unknown smoothness
by: Grill, Jean-Bastien, et al.
Published: (2026)
by: Grill, Jean-Bastien, et al.
Published: (2026)
Statistical inference on black-box generative models in the data kernel perspective space
by: Helm, Hayden, et al.
Published: (2024)
by: Helm, Hayden, et al.
Published: (2024)
Domain Bridge: Generative model-based domain forensic for black-box models
by: Zhang, Jiyi, et al.
Published: (2024)
by: Zhang, Jiyi, et al.
Published: (2024)
Collaborative and Federated Black-box Optimization: A Bayesian Optimization Perspective
by: Kontar, Raed Al
Published: (2024)
by: Kontar, Raed Al
Published: (2024)
CPT: Consistent Proxy Tuning for Black-box Optimization
by: He, Yuanyang, et al.
Published: (2024)
by: He, Yuanyang, et al.
Published: (2024)
Upper Entropy for 2-Monotone Lower Probabilities
by: Vu, Tuan-Anh, et al.
Published: (2026)
by: Vu, Tuan-Anh, et al.
Published: (2026)
Locality-aware Surrogates for Gradient-based Black-box Optimization
by: Momeni, Ali, et al.
Published: (2025)
by: Momeni, Ali, et al.
Published: (2025)
High Dimensional Bayesian Optimization using Lasso Variable Selection
by: Hoang, Vu Viet, et al.
Published: (2025)
by: Hoang, Vu Viet, et al.
Published: (2025)
Inside the black box: Neural network-based real-time prediction of US recessions
by: Chung, Seulki
Published: (2023)
by: Chung, Seulki
Published: (2023)
VOPy: A Framework for Black-box Vector Optimization
by: Yıldırım, Yaşar Cahit, et al.
Published: (2024)
by: Yıldırım, Yaşar Cahit, et al.
Published: (2024)
Hoeffding decomposition of black-box models with dependent inputs
by: Idrissi, Marouane Il, et al.
Published: (2023)
by: Idrissi, Marouane Il, et al.
Published: (2023)
Towards more transferable adversarial attack in black-box manner
by: Lei, Chun Tong, et al.
Published: (2025)
by: Lei, Chun Tong, et al.
Published: (2025)
Explore the vulnerability of black-box models via diffusion models
by: Shi, Jiacheng, et al.
Published: (2025)
by: Shi, Jiacheng, et al.
Published: (2025)
Surrogate modeling for interpreting black-box LLMs in medical predictions
by: Han, Changho, et al.
Published: (2026)
by: Han, Changho, et al.
Published: (2026)
Posterior Inference in Latent Space for Scalable Constrained Black-box Optimization
by: Om, Kiyoung, et al.
Published: (2025)
by: Om, Kiyoung, et al.
Published: (2025)
Posterior Inference with Diffusion Models for High-dimensional Black-box Optimization
by: Yun, Taeyoung, et al.
Published: (2025)
by: Yun, Taeyoung, et al.
Published: (2025)
Covariance-Adaptive Sequential Black-box Optimization for Diffusion Targeted Generation
by: Lyu, Yueming, et al.
Published: (2024)
by: Lyu, Yueming, et al.
Published: (2024)
OpenBox: A Python Toolkit for Generalized Black-box Optimization
by: Jiang, Huaijun, et al.
Published: (2023)
by: Jiang, Huaijun, et al.
Published: (2023)
An Open-Source Training Dataset for Foundation Models for Black-box Optimization
by: Klein, Aaron, et al.
Published: (2026)
by: Klein, Aaron, et al.
Published: (2026)
Gaussian-Mixture-Model Q-Functions for Reinforcement Learning by Riemannian Optimization
by: Vu, Minh, et al.
Published: (2024)
by: Vu, Minh, et al.
Published: (2024)
Black-box Optimization with Simultaneous Statistical Inference for Optimal Performance
by: Lian, Teng, et al.
Published: (2025)
by: Lian, Teng, et al.
Published: (2025)
Low-rank surrogate modeling and stochastic zero-order optimization for training of neural networks with black-box layers
by: Chertkov, Andrei, et al.
Published: (2025)
by: Chertkov, Andrei, et al.
Published: (2025)
Black-box Optimization of LLM Outputs by Asking for Directions
by: Zhang, Jie, et al.
Published: (2025)
by: Zhang, Jie, et al.
Published: (2025)
Modular addition without black-boxes: Compressing explanations of MLPs that compute numerical integration
by: Yip, Chun Hei, et al.
Published: (2024)
by: Yip, Chun Hei, et al.
Published: (2024)
Optimizing importance weighting in the presence of sub-population shifts
by: Holstege, Floris, et al.
Published: (2024)
by: Holstege, Floris, et al.
Published: (2024)
Similar Items
-
Towards black-box parameter estimation
by: Lenzi, Amanda, et al.
Published: (2023) -
Time-Aware Latent Space Bayesian Optimization
by: Vu, Tuan A., et al.
Published: (2026) -
Towards consistency of rule-based explainer and black box model -- fusion of rule induction and XAI-based feature importance
by: Kozielski, Michał, et al.
Published: (2024) -
Gradients of unitary optical neural networks using parameter-shift rule
by: Jiang, Jinzhe, et al.
Published: (2025) -
Investigating Bayesian optimization for expensive-to-evaluate black box functions: Application in fluid dynamics
by: Diessner, Mike, et al.
Published: (2022)