Fast, Scalable, Warm-Start Semidefinite Programming with Spectral Bundling and Sketching
Fuente:
arXiv
Saved in:
| Main Authors: | Angell, Rico, McCallum, Andrew |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Low-Rank Extragradient Methods for Scalable Semidefinite Optimization
by: Garber, Dan, et al.
Published: (2024)
by: Garber, Dan, et al.
Published: (2024)
An Overview and Comparison of Spectral Bundle Methods for Primal and Dual Semidefinite Programs
by: Liao, Feng-Yi, et al.
Published: (2023)
by: Liao, Feng-Yi, et al.
Published: (2023)
A Semidefinite Programming-Based Branch-and-Cut Algorithm for Biclustering
by: Sudoso, Antonio M.
Published: (2024)
by: Sudoso, Antonio M.
Published: (2024)
Mixtures Closest to a Given Measure: A Semidefinite Programming Approach
by: Đurašinović, Srećko, et al.
Published: (2025)
by: Đurašinović, Srećko, et al.
Published: (2025)
Deconfounded Warm-Start Thompson Sampling with Applications to Precision Medicine
by: Jaiswal, Prateek, et al.
Published: (2025)
by: Jaiswal, Prateek, et al.
Published: (2025)
Statistically Optimal K-means Clustering via Nonnegative Low-rank Semidefinite Programming
by: Zhuang, Yubo, et al.
Published: (2023)
by: Zhuang, Yubo, et al.
Published: (2023)
Semidefinite Relaxations of the Gromov-Wasserstein Distance
by: Chen, Junyu, et al.
Published: (2023)
by: Chen, Junyu, et al.
Published: (2023)
Heuristic Bundle Upper Bound Based Polyhedral Bundle Method for Semidefinite Programming
by: Cui, Zilong, et al.
Published: (2025)
by: Cui, Zilong, et al.
Published: (2025)
WARP: A Benchmark for Primal-Dual Warm-Starting of Interior-Point Solvers
by: Suri, Dhruv, et al.
Published: (2026)
by: Suri, Dhruv, et al.
Published: (2026)
Statistical Inference of Constrained Stochastic Optimization via Sketched Sequential Quadratic Programming
by: Na, Sen, et al.
Published: (2022)
by: Na, Sen, et al.
Published: (2022)
Bundle Network: a Machine Learning-Based Bundle Method
by: Demelas, Francesca, et al.
Published: (2025)
by: Demelas, Francesca, et al.
Published: (2025)
Learning to Price Bundles: A GCN Approach for Mixed Bundling
by: Ding, Liangyu, et al.
Published: (2025)
by: Ding, Liangyu, et al.
Published: (2025)
Dual Conic Proxy for Semidefinite Relaxation of AC Optimal Power Flow
by: Qiu, Guancheng, et al.
Published: (2025)
by: Qiu, Guancheng, et al.
Published: (2025)
Towards Optimal Branching of Linear and Semidefinite Relaxations for Neural Network Robustness Certification
by: Anderson, Brendon G., et al.
Published: (2021)
by: Anderson, Brendon G., et al.
Published: (2021)
Learning-Augmented Scalable Linear Assignment Problem Optimization via Neural Dual Warm-Starts
by: Yavlovich, Ilay, et al.
Published: (2026)
by: Yavlovich, Ilay, et al.
Published: (2026)
Improved Approximation Algorithms for Orthogonally Constrained Problems Using Semidefinite Optimization
by: Cory-Wright, Ryan, et al.
Published: (2025)
by: Cory-Wright, Ryan, et al.
Published: (2025)
Turbocharging Gaussian Process Inference with Approximate Sketch-and-Project
by: Rathore, Pratik, et al.
Published: (2025)
by: Rathore, Pratik, et al.
Published: (2025)
A Sketch-and-Project Analysis of Subsampled Natural Gradient Algorithms
by: Goldshlager, Gil, et al.
Published: (2025)
by: Goldshlager, Gil, et al.
Published: (2025)
A conditional gradient homotopy method with applications to Semidefinite Programming
by: Dvurechensky, Pavel, et al.
Published: (2022)
by: Dvurechensky, Pavel, et al.
Published: (2022)
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)
Why Do We Need Warm-up? A Theoretical Perspective
by: Alimisis, Foivos, et al.
Published: (2025)
by: Alimisis, Foivos, et al.
Published: (2025)
CaVE: A Cone-Aligned Approach for Fast Predict-then-optimize with Binary Linear Programs
by: Tang, Bo, et al.
Published: (2023)
by: Tang, Bo, et al.
Published: (2023)
Inference of Online Newton Methods with Nesterov's Accelerated Sketching
by: Wang, Haoxuan, et al.
Published: (2026)
by: Wang, Haoxuan, et al.
Published: (2026)
Where Does Warm-Up Come From? Adaptive Scheduling for Norm-Constrained Optimizers
by: Riabinin, Artem, et al.
Published: (2026)
by: Riabinin, Artem, et al.
Published: (2026)
Sketch-and-Project Meets Newton Method: Global $\mathcal O(k^{-2})$ Convergence with Low-Rank Updates
by: Hanzely, Slavomír
Published: (2023)
by: Hanzely, Slavomír
Published: (2023)
Learning to Solve the Quadratic Assignment Problem with Warm-Started MCMC Finetuning
by: Pan, Yicheng, et al.
Published: (2026)
by: Pan, Yicheng, et al.
Published: (2026)
ECPv2: Fast, Efficient, and Scalable Global Optimization of Lipschitz Functions
by: Fourati, Fares, et al.
Published: (2025)
by: Fourati, Fares, et al.
Published: (2025)
Scalable Decentralized Learning with Teleportation
by: Takezawa, Yuki, et al.
Published: (2025)
by: Takezawa, Yuki, et al.
Published: (2025)
Scalable Kernel Inverse Optimization
by: Long, Youyuan, et al.
Published: (2024)
by: Long, Youyuan, et al.
Published: (2024)
Scalable Online Exploration via Coverability
by: Amortila, Philip, et al.
Published: (2024)
by: Amortila, Philip, et al.
Published: (2024)
Learning to Configure Mathematical Programming Solvers by Mathematical Programming
by: Iommazzo, Gabriele, et al.
Published: (2024)
by: Iommazzo, Gabriele, et al.
Published: (2024)
Convergence of Spectral Descent for Non-smooth Optimization
by: Yang, Yixuan, et al.
Published: (2026)
by: Yang, Yixuan, et al.
Published: (2026)
Muon Optimizes Under Spectral Norm Constraints
by: Chen, Lizhang, et al.
Published: (2025)
by: Chen, Lizhang, et al.
Published: (2025)
Towards Scalable Semidefinite Programming: Optimal Metric ADMM with A Worst-case Performance Guarantee
by: Ran, Yifan, et al.
Published: (2024)
by: Ran, Yifan, et al.
Published: (2024)
DNNLasso: Scalable Graph Learning for Matrix-Variate Data
by: Lin, Meixia, et al.
Published: (2024)
by: Lin, Meixia, et al.
Published: (2024)
Scalable Approximate Algorithms for Optimal Transport Linear Models
by: Kacprzak, Tomasz, et al.
Published: (2025)
by: Kacprzak, Tomasz, et al.
Published: (2025)
Constrained Stochastic Spectral Preconditioning Converges for Nonconvex Objectives
by: Oikonomidis, Konstantinos, et al.
Published: (2026)
by: Oikonomidis, Konstantinos, et al.
Published: (2026)
SOREL: A Stochastic Algorithm for Spectral Risks Minimization
by: Ge, Yuze, et al.
Published: (2024)
by: Ge, Yuze, et al.
Published: (2024)
Disciplined Geodesically Convex Programming
by: Cheng, Andrew, et al.
Published: (2024)
by: Cheng, Andrew, et al.
Published: (2024)
Improved Scalable Lipschitz Bounds for Deep Neural Networks
by: Syed, Usman, et al.
Published: (2025)
by: Syed, Usman, et al.
Published: (2025)
Similar Items
-
Low-Rank Extragradient Methods for Scalable Semidefinite Optimization
by: Garber, Dan, et al.
Published: (2024) -
An Overview and Comparison of Spectral Bundle Methods for Primal and Dual Semidefinite Programs
by: Liao, Feng-Yi, et al.
Published: (2023) -
A Semidefinite Programming-Based Branch-and-Cut Algorithm for Biclustering
by: Sudoso, Antonio M.
Published: (2024) -
Mixtures Closest to a Given Measure: A Semidefinite Programming Approach
by: Đurašinović, Srećko, et al.
Published: (2025) -
Deconfounded Warm-Start Thompson Sampling with Applications to Precision Medicine
by: Jaiswal, Prateek, et al.
Published: (2025)