Saved in:
| Main Authors: | Ma, Xinge, Wang, Jin, Zhang, Xuejie |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2503.06028 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Sample-aware Adaptive Structured Pruning for Large Language Models
by: Kong, Jun, et al.
Published: (2025)
by: Kong, Jun, et al.
Published: (2025)
On the Optimal Construction of Unbiased Gradient Estimators for Zeroth-Order Optimization
by: Ma, Shaocong, et al.
Published: (2025)
by: Ma, Shaocong, et al.
Published: (2025)
Efficient Federated RLHF via Zeroth-Order Policy Optimization
by: Wang, Deyi, et al.
Published: (2026)
by: Wang, Deyi, et al.
Published: (2026)
Achieving Dimension-Free Communication in Federated Learning via Zeroth-Order Optimization
by: Li, Zhe, et al.
Published: (2024)
by: Li, Zhe, et al.
Published: (2024)
Powering Up Zeroth-Order Training via Subspace Gradient Orthogonalization
by: Lang, Yicheng, et al.
Published: (2026)
by: Lang, Yicheng, et al.
Published: (2026)
Riemannian Zeroth-Order Gradient Estimation with Structure-Preserving Metrics for Geodesically Incomplete Manifolds
by: Ma, Shaocong, et al.
Published: (2026)
by: Ma, Shaocong, et al.
Published: (2026)
ZOTTA: Test-Time Adaptation with Gradient-Free Zeroth-Order Optimization
by: Zhang, Ronghao, et al.
Published: (2026)
by: Zhang, Ronghao, et al.
Published: (2026)
Fed-ZOE: Communication-Efficient Over-the-Air Federated Learning via Zeroth-Order Estimation
by: Jang, Jonggyu, et al.
Published: (2024)
by: Jang, Jonggyu, et al.
Published: (2024)
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)
Gradient Compressed Sensing: A Query-Efficient Gradient Estimator for High-Dimensional Zeroth-Order Optimization
by: Qiu, Ruizhong, et al.
Published: (2024)
by: Qiu, Ruizhong, et al.
Published: (2024)
BB-Patch: BlackBox Adversarial Patch-Attack using Zeroth-Order Optimization
by: Kumar, Satyadwyoom, et al.
Published: (2024)
by: Kumar, Satyadwyoom, et al.
Published: (2024)
Zeroth-Order Policy Gradient for Reinforcement Learning from Human Feedback without Reward Inference
by: Zhang, Qining, et al.
Published: (2024)
by: Zhang, Qining, et al.
Published: (2024)
Zeroth-Order Hard-Thresholding: Gradient Error vs. Expansivity
by: de Vazelhes, William, et al.
Published: (2022)
by: de Vazelhes, William, et al.
Published: (2022)
On the Inherent Privacy of Zeroth Order Projected Gradient Descent
by: Gupta, Devansh, et al.
Published: (2025)
by: Gupta, Devansh, et al.
Published: (2025)
A Randomized Zeroth-Order Hierarchical Framework for Heterogeneous Federated Learning
by: Qiu, Yuyang, et al.
Published: (2025)
by: Qiu, Yuyang, et al.
Published: (2025)
Improving the Straight-Through Estimator with Zeroth-Order Information
by: Yang, Ningfeng, et al.
Published: (2025)
by: Yang, Ningfeng, et al.
Published: (2025)
On-Device Fine-Tuning via Backprop-Free Zeroth-Order Optimization
by: Katti, Prabodh, et al.
Published: (2025)
by: Katti, Prabodh, et al.
Published: (2025)
Private Zeroth-Order Optimization with Public Data
by: Gong, Xuchen, et al.
Published: (2025)
by: Gong, Xuchen, et al.
Published: (2025)
A Historical Trajectory Assisted Optimization Method for Zeroth-Order Federated Learning
by: Wu, Chenlin, et al.
Published: (2024)
by: Wu, Chenlin, et al.
Published: (2024)
Dimensional Peeking for Low-Variance Gradients in Zeroth-Order Discrete Optimization via Simulation
by: Andelfinger, Philipp, et al.
Published: (2026)
by: Andelfinger, Philipp, et al.
Published: (2026)
On the Convergence of Zeroth-Order Federated Tuning for Large Language Models
by: Ling, Zhenqing, et al.
Published: (2024)
by: Ling, Zhenqing, et al.
Published: (2024)
Position: Zeroth-Order Optimization in Deep Learning Is Underexplored, Not Underpowered
by: Liu, Sijia, et al.
Published: (2026)
by: Liu, Sijia, et al.
Published: (2026)
Learning a Zeroth-Order Optimizer for Fine-Tuning LLMs
by: Zhang, Kairun, et al.
Published: (2025)
by: Zhang, Kairun, et al.
Published: (2025)
Learning Surrogates for Offline Black-Box Optimization via Gradient Matching
by: Hoang, Minh, et al.
Published: (2025)
by: Hoang, Minh, et al.
Published: (2025)
Obtaining Lower Query Complexities through Lightweight Zeroth-Order Proximal Gradient Algorithms
by: Gu, Bin, et al.
Published: (2024)
by: Gu, Bin, et al.
Published: (2024)
Communication-Efficient and Differentially Private Vertical Federated Learning with Zeroth-Order Optimization
by: Zhang, Jianing, et al.
Published: (2025)
by: Zhang, Jianing, et al.
Published: (2025)
Z0-Inf: Zeroth Order Approximation for Data Influence
by: Kokhlikyan, Narine, et al.
Published: (2025)
by: Kokhlikyan, Narine, et al.
Published: (2025)
Black-Box Combinatorial Optimization with Order-Invariant Reinforcement Learning
by: Goudet, Olivier, et al.
Published: (2025)
by: Goudet, Olivier, et al.
Published: (2025)
Towards Fast LLM Fine-tuning through Zeroth-Order Optimization with Projected Gradient-Aligned Perturbations
by: Mi, Zhendong, et al.
Published: (2025)
by: Mi, Zhendong, et al.
Published: (2025)
Revisiting Zeroth-Order Optimization: Minimum-Variance Two-Point Estimators and Directionally Aligned Perturbations
by: Ma, Shaocong, et al.
Published: (2025)
by: Ma, Shaocong, et al.
Published: (2025)
Turning Stale Gradients into Stable Gradients: Coherent Coordinate Descent with Implicit Landscape Smoothing for Lightweight Zeroth-Order Optimization
by: Liang, Chen, et al.
Published: (2026)
by: Liang, Chen, et al.
Published: (2026)
Learning to Learn from APIs: Black-Box Data-Free Meta-Learning
by: Hu, Zixuan, et al.
Published: (2023)
by: Hu, Zixuan, et al.
Published: (2023)
On Adaptivity in Zeroth-Order Optimization
by: Dbouk, Hassan, et al.
Published: (2026)
by: Dbouk, Hassan, et al.
Published: (2026)
Mitigating Non-IID Drift in Zeroth-Order Federated LLM Fine-Tuning with Transferable Sparsity
by: Ran, Yide, et al.
Published: (2025)
by: Ran, Yide, et al.
Published: (2025)
When Foresight Pruning Meets Zeroth-Order Optimization: Efficient Federated Learning for Low-Memory Devices
by: Zhang, Pengyu, et al.
Published: (2024)
by: Zhang, Pengyu, et al.
Published: (2024)
Warming Up for Zeroth-Order Federated Pre-Training with Low Resource Clients
by: Legate, Gwen, et al.
Published: (2025)
by: Legate, Gwen, et al.
Published: (2025)
Generalized and Personalized Federated Learning with Black-Box Foundation Models via Orthogonal Transformations
by: Kong, Eun Gyung, et al.
Published: (2025)
by: Kong, Eun Gyung, et al.
Published: (2025)
A Zeroth-Order Extra-Gradient Method for Black-Box Constrained Optimization
by: Zhou, Yuke, et al.
Published: (2025)
by: Zhou, Yuke, et al.
Published: (2025)
Learning Dynamics of Zeroth-Order Optimization: A Kernel Perspective
by: Li, Zhe, et al.
Published: (2026)
by: Li, Zhe, et al.
Published: (2026)
Accelerating Zeroth-Order Spectral Optimization with Partial Orthogonalization from Power Iteration
by: Chen, Jiahe, et al.
Published: (2026)
by: Chen, Jiahe, et al.
Published: (2026)
Similar Items
-
Sample-aware Adaptive Structured Pruning for Large Language Models
by: Kong, Jun, et al.
Published: (2025) -
On the Optimal Construction of Unbiased Gradient Estimators for Zeroth-Order Optimization
by: Ma, Shaocong, et al.
Published: (2025) -
Efficient Federated RLHF via Zeroth-Order Policy Optimization
by: Wang, Deyi, et al.
Published: (2026) -
Achieving Dimension-Free Communication in Federated Learning via Zeroth-Order Optimization
by: Li, Zhe, et al.
Published: (2024) -
Powering Up Zeroth-Order Training via Subspace Gradient Orthogonalization
by: Lang, Yicheng, et al.
Published: (2026)