Blessing of Nonconvexity in Deep Linear Models: Depth Flattens the Optimization Landscape Around the True Solution

15 July 2022

Papers citing "Blessing of Nonconvexity in Deep Linear Models: Depth Flattens the Optimization Landscape Around the True Solution"

7 / 7 papers shown

Title
Mitigating Label Noise through Data Ambiguation Julian Lienen Eyke Hüllermeier NoLa 15 6 0 23 May 2023
Behind the Scenes of Gradient Descent: A Trajectory Analysis via Basis Function Decomposition Jianhao Ma Li-Zhen Guo S. Fattahi 19 4 0 01 Oct 2022
Preconditioned Gradient Descent for Overparameterized Nonconvex Burer--Monteiro Factorization with Global Optimality Certification G. Zhang S. Fattahi Richard Y. Zhang 32 23 0 07 Jun 2022
Robust Training under Label Noise by Over-parameterization Sheng Liu Zhihui Zhu Qing Qu Chong You NoLa OOD 8 105 0 28 Feb 2022
Optimization-Based Separations for Neural Networks Itay Safran Jason D. Lee 82 14 0 04 Dec 2021
Rank Overspecified Robust Matrix Recovery: Subgradient Method and Exact Recovery Lijun Ding Liwei Jiang Yudong Chen Qing Qu Zhihui Zhu 18 28 0 23 Sep 2021
Benefits of depth in neural networks Matus Telgarsky 123 600 0 14 Feb 2016