Saved in:
| Main Authors: | Zhang, Hongyang R., Zhang, Zhenshuo, Nguyen, Huy L., Lan, Guanghui |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2601.12213 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
WinQ: Accelerating Quantization-Aware Training of Language Models Around Saddle Points
by: Li, Dongyue, et al.
Published: (2026)
by: Li, Dongyue, et al.
Published: (2026)
Stochastic Auto-conditioned Fast Gradient Methods with Optimal Rates
by: Ji, Yao, et al.
Published: (2026)
by: Ji, Yao, et al.
Published: (2026)
Auto-conditioned primal-dual hybrid gradient method and alternating direction method of multipliers
by: Lan, Guanghui, et al.
Published: (2024)
by: Lan, Guanghui, et al.
Published: (2024)
A simple uniformly optimal method without line search for convex optimization
by: Li, Tianjiao, et al.
Published: (2023)
by: Li, Tianjiao, et al.
Published: (2023)
On the Robustness of Cross-Concentrated Sampling for Matrix Completion
by: Cai, HanQin, et al.
Published: (2024)
by: Cai, HanQin, et al.
Published: (2024)
Value Mirror Descent for Reinforcement Learning
by: Jia, Zhichao, et al.
Published: (2026)
by: Jia, Zhichao, et al.
Published: (2026)
Projected gradient methods for nonconvex and stochastic smooth optimization: new complexities and auto-conditioned stepsizes
by: Lan, Guanghui, et al.
Published: (2024)
by: Lan, Guanghui, et al.
Published: (2024)
Can SGD Handle Heavy-Tailed Noise?
by: Fatkhullin, Ilyas, et al.
Published: (2025)
by: Fatkhullin, Ilyas, et al.
Published: (2025)
Stochastic first-order methods for average-reward Markov decision processes
by: Li, Tianjiao, et al.
Published: (2022)
by: Li, Tianjiao, et al.
Published: (2022)
Machine Learning Model for Sparse PCM Completion
by: Koyuncu, Selcuk, et al.
Published: (2026)
by: Koyuncu, Selcuk, et al.
Published: (2026)
Convergence Rate Analysis of the AdamW-Style Shampoo: Unifying One-Sided and Two-Sided Preconditioning
by: Li, Huan, et al.
Published: (2026)
by: Li, Huan, et al.
Published: (2026)
Projection-Free Functional Constrained Optimization for Risk Aversion and Sparsity Control
by: Cheng, Yi, et al.
Published: (2022)
by: Cheng, Yi, et al.
Published: (2022)
Convergence of Gradient Descent with Small Initialization for Unregularized Matrix Completion
by: Ma, Jianhao, et al.
Published: (2024)
by: Ma, Jianhao, et al.
Published: (2024)
Stochastic Constrained Decentralized Optimization for Machine Learning with Fewer Data Oracles: a Gradient Sliding Approach
by: Nguyen, Hoang Huy, et al.
Published: (2024)
by: Nguyen, Hoang Huy, et al.
Published: (2024)
Majorization-minimization for Sparse Nonnegative Matrix Factorization with the $β$-divergence
by: Marmin, Arthur, et al.
Published: (2022)
by: Marmin, Arthur, et al.
Published: (2022)
Accelerated stochastic approximation with state-dependent noise
by: Ilandarideva, Sasila, et al.
Published: (2023)
by: Ilandarideva, Sasila, et al.
Published: (2023)
Matrix Completion with Graph Information: A Provable Nonconvex Optimization Approach
by: Wang, Yao, et al.
Published: (2025)
by: Wang, Yao, et al.
Published: (2025)
Disjunctive Branch-and-Bound for Certifiably Optimal Low-Rank Matrix Completion
by: Bertsimas, Dimitris, et al.
Published: (2023)
by: Bertsimas, Dimitris, et al.
Published: (2023)
Learning Large Causal Structures from Inverse Covariance Matrix via Sparse Matrix Decomposition
by: Dong, Shuyu, et al.
Published: (2022)
by: Dong, Shuyu, et al.
Published: (2022)
Sparse Hyperparametric Itakura-Saito Nonnegative Matrix Factorization via Bi-Level Optimization
by: Selicato, Laura, et al.
Published: (2025)
by: Selicato, Laura, et al.
Published: (2025)
Lean and Mean Adaptive Optimization via Subset-Norm and Subspace-Momentum with Convergence Guarantees
by: Nguyen, Thien Hang, et al.
Published: (2024)
by: Nguyen, Thien Hang, et al.
Published: (2024)
SPP-SBL: Space-Power Prior Sparse Bayesian Learning for Block Sparse Recovery
by: Zhang, Yanhao, et al.
Published: (2025)
by: Zhang, Yanhao, et al.
Published: (2025)
Universal Online Convex Optimization Meets Second-order Bounds
by: Zhang, Lijun, et al.
Published: (2021)
by: Zhang, Lijun, et al.
Published: (2021)
Low Rank Matrix Completion via Robust Alternating Minimization in Nearly Linear Time
by: Gu, Yuzhou, et al.
Published: (2023)
by: Gu, Yuzhou, et al.
Published: (2023)
Preconditioned Gradient Descent for Over-Parameterized Nonconvex Matrix Factorization
by: Zhang, Gavin, et al.
Published: (2025)
by: Zhang, Gavin, et al.
Published: (2025)
Controllable Expensive Multi-objective Learning with Warm-starting Bayesian Optimization
by: Nguyen, Quang-Huy, et al.
Published: (2023)
by: Nguyen, Quang-Huy, et al.
Published: (2023)
DNNLasso: Scalable Graph Learning for Matrix-Variate Data
by: Lin, Meixia, et al.
Published: (2024)
by: Lin, Meixia, et al.
Published: (2024)
Noise Stability Optimization for Finding Flat Minima: A Hessian-based Regularization Approach
by: Zhang, Hongyang R., et al.
Published: (2023)
by: Zhang, Hongyang R., et al.
Published: (2023)
Nonnegative Low-rank Matrix Recovery Can Have Spurious Local Minima
by: Zhang, Richard Y.
Published: (2025)
by: Zhang, Richard Y.
Published: (2025)
Block Sparse Bayesian Learning: A Diversified Scheme
by: Zhang, Yanhao, et al.
Published: (2024)
by: Zhang, Yanhao, et al.
Published: (2024)
Fast and Effective Computation of Generalized Symmetric Matrix Factorization
by: Yang, Lei, et al.
Published: (2026)
by: Yang, Lei, et al.
Published: (2026)
A Global Optimization Algorithm for K-Center Clustering of One Billion Samples
by: Ren, Jiayang, et al.
Published: (2022)
by: Ren, Jiayang, et al.
Published: (2022)
Provable Non-Convex Euclidean Distance Matrix Completion: Geometry, Reconstruction, and Robustness
by: Smith, Chandler, et al.
Published: (2025)
by: Smith, Chandler, et al.
Published: (2025)
Completely Parameter-Free Single-Loop Algorithms for Nonconvex-Concave Minimax Problems
by: Yang, Junnan, et al.
Published: (2024)
by: Yang, Junnan, et al.
Published: (2024)
Enhancing Accuracy in Deep Learning Using Random Matrix Theory
by: Berlyand, Leonid, et al.
Published: (2023)
by: Berlyand, Leonid, et al.
Published: (2023)
Sparse-ProxSkip: Accelerated Sparse-to-Sparse Training in Federated Learning
by: Meinhardt, Georg, et al.
Published: (2024)
by: Meinhardt, Georg, et al.
Published: (2024)
Nonnegative Matrix Factorization in the Component-Wise L1 Norm for Sparse Data
by: Seraghiti, Giovanni, et al.
Published: (2026)
by: Seraghiti, Giovanni, et al.
Published: (2026)
Two-Timescale Optimization Framework for Sparse-Feedback Linear-Quadratic Optimal Control
by: Feng, Lechen, et al.
Published: (2024)
by: Feng, Lechen, et al.
Published: (2024)
Reheated Gradient-based Discrete Sampling for Combinatorial Optimization
by: Li, Muheng, et al.
Published: (2025)
by: Li, Muheng, et al.
Published: (2025)
Time-varying Mixing Matrix Design for Energy-efficient Decentralized Federated Learning
by: Zhang, Xusheng, et al.
Published: (2025)
by: Zhang, Xusheng, et al.
Published: (2025)
Similar Items
-
WinQ: Accelerating Quantization-Aware Training of Language Models Around Saddle Points
by: Li, Dongyue, et al.
Published: (2026) -
Stochastic Auto-conditioned Fast Gradient Methods with Optimal Rates
by: Ji, Yao, et al.
Published: (2026) -
Auto-conditioned primal-dual hybrid gradient method and alternating direction method of multipliers
by: Lan, Guanghui, et al.
Published: (2024) -
A simple uniformly optimal method without line search for convex optimization
by: Li, Tianjiao, et al.
Published: (2023) -
On the Robustness of Cross-Concentrated Sampling for Matrix Completion
by: Cai, HanQin, et al.
Published: (2024)