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Bibliografiske detaljer
Main Authors:	Ma, Shaocong, Huang, Heng
Format:	Preprint
Udgivet:	2026
Fag:	Machine Learning Optimization and Control
Online adgang:	https://arxiv.org/abs/2601.08039
Tags:	Tilføj Tag Ingen Tags, Vær først til at tagge denne postø!

Lignende værker

On the Optimal Construction of Unbiased Gradient Estimators for Zeroth-Order Optimization
af: Ma, Shaocong, et al.
Udgivet: (2025)

Revisiting Zeroth-Order Optimization: Minimum-Variance Two-Point Estimators and Directionally Aligned Perturbations
af: Ma, Shaocong, et al.
Udgivet: (2025)

Obtaining Lower Query Complexities through Lightweight Zeroth-Order Proximal Gradient Algorithms
af: Gu, Bin, et al.
Udgivet: (2024)

Robust Reinforcement Learning in Finance: Modeling Market Impact with Elliptic Uncertainty Sets
af: Ma, Shaocong, et al.
Udgivet: (2025)

Zeroth-Order Methods for Stochastic Nonconvex Nonsmooth Composite Optimization
af: Chen, Ziyi, et al.
Udgivet: (2025)

Decentralized Riemannian Conjugate Gradient Method on the Stiefel Manifold
af: Chen, Jun, et al.
Udgivet: (2023)

On the Inherent Privacy of Zeroth Order Projected Gradient Descent
af: Gupta, Devansh, et al.
Udgivet: (2025)

Zeroth-Order Hard-Thresholding: Gradient Error vs. Expansivity
af: de Vazelhes, William, et al.
Udgivet: (2022)

New Hybrid Fine-Tuning Paradigm for LLMs: Algorithm Design and Convergence Analysis Framework
af: Ma, Shaocong, et al.
Udgivet: (2026)

On Adaptivity in Zeroth-Order Optimization
af: Dbouk, Hassan, et al.
Udgivet: (2026)

VAMO: Efficient Zeroth-Order Variance Reduction for SGD with Faster Convergence
af: Chen, Jiahe, et al.
Udgivet: (2025)

Federated Learning on Riemannian Manifolds: A Gradient-Free Projection-Based Approach
af: Wang, Hongye, et al.
Udgivet: (2025)

Mirror Descent on Riemannian Manifolds
af: Jiang, Jiaxin, et al.
Udgivet: (2026)

Zeroth-Order primal-dual Alternating Projection Gradient Algorithms for Nonconvex Minimax Problems with Coupled linear Constraints
af: Zhang, Huiling, et al.
Udgivet: (2024)

LORENZA: Enhancing Generalization in Low-Rank Gradient LLM Training via Efficient Zeroth-Order Adaptive SAM
af: Refael, Yehonathan, et al.
Udgivet: (2025)

Fully Zeroth-Order Bilevel Programming via Gaussian Smoothing
af: Aghasi, Alireza, et al.
Udgivet: (2024)

Zeroth-Order Optimization at the Edge of Stability
af: Song, Minhak, et al.
Udgivet: (2026)

A Framework for Bilevel Optimization on Riemannian Manifolds
af: Han, Andi, et al.
Udgivet: (2024)

Geometry-Preserving Neural Architectures on Manifolds with Boundary
af: Elamvazhuthi, Karthik, et al.
Udgivet: (2026)

A Randomized Zeroth-Order Hierarchical Framework for Heterogeneous Federated Learning
af: Qiu, Yuyang, et al.
Udgivet: (2025)

Minimisation of Polyak-Łojasewicz Functions Using Random Zeroth-Order Oracles
af: Farzin, Amir Ali, et al.
Udgivet: (2024)

Stochastic Zeroth order Descent with Structured Directions
af: Rando, Marco, et al.
Udgivet: (2022)

Fast, Accurate Manifold Denoising by Tunneling Riemannian Optimization
af: Wang, Shiyu, et al.
Udgivet: (2025)

Zeroth-Order Optimization Finds Flat Minima
af: Zhang, Liang, et al.
Udgivet: (2025)

Certified Multi-Fidelity Zeroth-Order Optimization
af: de Montbrun, Étienne, et al.
Udgivet: (2023)

Private Zeroth-Order Nonsmooth Nonconvex Optimization
af: Zhang, Qinzi, et al.
Udgivet: (2024)

Zeroth-Order Stochastic Mirror Descent Algorithms for Minimax Excess Risk Optimization
af: Gu, Zhihao, et al.
Udgivet: (2024)

Non-Uniform Noise-to-Signal Ratio in the REINFORCE Policy-Gradient Estimator
af: Han, Haoyu, et al.
Udgivet: (2026)

Learning-Rate-Free Stochastic Optimization over Riemannian Manifolds
af: Dodd, Daniel, et al.
Udgivet: (2024)

Gradient Flows and Riemannian Structure in the Gromov-Wasserstein Geometry
af: Zhang, Zhengxin, et al.
Udgivet: (2024)

Finite-Time Analysis of Stochastic Nonconvex Nonsmooth Optimization on the Riemannian Manifolds
af: Sahinoglu, Emre, et al.
Udgivet: (2025)

Riemannian Stochastic Gradient Method for Nested Composition Optimization
af: Zhang, Dewei, et al.
Udgivet: (2022)

Single Point-Based Distributed Zeroth-Order Optimization with a Non-Convex Stochastic Objective Function
af: Mhanna, Elissa, et al.
Udgivet: (2024)

Stochastic Zeroth-Order Optimization under Strongly Convexity and Lipschitz Hessian: Minimax Sample Complexity
af: Yu, Qian, et al.
Udgivet: (2024)

Decentralized Optimization on Compact Submanifolds by Quantized Riemannian Gradient Tracking
af: Chen, Jun, et al.
Udgivet: (2025)

Minimisation of Submodular Functions Using Gaussian Zeroth-Order Random Oracles
af: Farzin, Amir Ali, et al.
Udgivet: (2025)

Decentralized Online Riemannian Optimization Beyond Hadamard Manifolds
af: Sahinoglu, Emre, et al.
Udgivet: (2025)

Riemannian Dueling Optimization
af: Ren, Yuxuan, et al.
Udgivet: (2026)

ZORMS-LfD: Learning from Demonstrations with Zeroth-Order Random Matrix Search
af: Dry, Olivia, et al.
Udgivet: (2025)

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence
af: Jiao, Yang, et al.
Udgivet: (2024)