{"total":19,"rows":[{"id":"2206.03345","title":"Preconditioned Gradient Descent for Overparameterized Nonconvex Burer--Monteiro Factorization with Global Optimality Certification","created":"2022-06-07","cited_by_count":21,"area":null},{"id":"2207.01789","title":"Improved Global Guarantees for the Nonconvex Burer--Monteiro Factorization via Rank Overparameterization","created":"2022-07-05","cited_by_count":13,"area":null},{"id":"2310.00526","title":"Are Graph Neural Networks Optimal Approximation Algorithms?","created":"2023-10-01","cited_by_count":11,"area":null},{"id":"2108.01772","title":"Nonconvex Factorization and Manifold Formulations are Almost Equivalent in Low-rank Matrix Optimization","created":"2021-08-03","cited_by_count":4,"area":null},{"id":"2209.15130","title":"Nonconvex Matrix Factorization is Geodesically Convex: Global Landscape Analysis for Fixed-rank Matrix Optimization From a Riemannian Perspective","created":"2022-09-29","cited_by_count":4,"area":null},{"id":"2211.17244","title":"Tight Certification of Adversarially Trained Neural Networks via Nonconvex Low-Rank Semidefinite Relaxations","created":"2022-11-30","cited_by_count":4,"area":null},{"id":"2202.04026","title":"Low-Rank Extragradient Method for Nonsmooth and Low-Rank Matrix Optimization Problems","created":"2022-02-08","cited_by_count":3,"area":null},{"id":"2509.21675","title":"Scalable Second-order Riemannian Optimization for $K$-means Clustering","created":"2025-09-25","cited_by_count":2,"area":null},{"id":"2106.15493","title":"Generalized Orthogonal Procrustes Problem under Arbitrary Adversaries","created":"2021-06-29","cited_by_count":1,"area":null},{"id":"2112.13269","title":"Over-Parametrized Matrix Factorization in the Presence of Spurious Stationary Points","created":"2021-12-25","cited_by_count":1,"area":null},{"id":"2501.16322","title":"Implicit Bias in Matrix Factorization and its Explicit Realization in a New Architecture","created":"2025-01-27","cited_by_count":1,"area":null},{"id":"2101.02776","title":"The Nonconvex Geometry of Linear Inverse Problems","created":"2021-01-07","cited_by_count":0,"area":null},{"id":"2206.11523","title":"Low-Rank Mirror-Prox for Nonsmooth and Low-Rank Matrix Optimization Problems","created":"2022-06-23","cited_by_count":0,"area":null},{"id":"2406.10407","title":"Suboptimality bounds for trace-bounded SDPs enable a faster and scalable low-rank SDP solver SDPLR+","created":"2024-06-14","cited_by_count":0,"area":null},{"id":"2410.19844","title":"A practical, fast method for solving sum-of-squares problems for very large polynomials","created":"2024-10-21","cited_by_count":0,"area":null},{"id":"2411.03103","title":"Benign landscape for Burer-Monteiro factorizations of MaxCut-type semidefinite programs","created":"2024-11-05","cited_by_count":0,"area":null},{"id":"2508.05493","title":"Exact and Heuristic Algorithms for Constrained Biclustering","created":"2025-08-07","cited_by_count":0,"area":null},{"id":"2610.12829","title":"Scalable Learning of Determinantal Point Processes with Kernel-Structured Interactions","created":"2026-10-09","cited_by_count":0,"area":null},{"id":"2610.18318","title":"Over-parameterization Is Neither Robust nor Fragile in Matrix Sensing: A Geometric Theory of Solution Robustness","created":"2026-10-13","cited_by_count":0,"area":null}],"next_cursor":null}