Low-loss connection of weight vectors: distribution-based approaches
Ivan Anokhin, Dmitry Yarotsky
Abstract
Recent research shows that sublevel sets of the loss surfaces of overparameterized networks are connected, exactly or approximately. We describe and compare experimentally a panel of methods used to connect two low-loss points by a low-loss curve on this surface. Our methods vary in accuracy and complexity. Most of our methods are based on "macroscopic" distributional assumptions, and some are insensitive to the detailed properties of the points to be connected. Some methods require a prior training of a "global connection model" which can then be applied to any pair of points. The accuracy of the method generally correlates with its complexity and sensitivity to the endpoint detail.
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Cited by top-tier papers1
Ask how each one uses itRelated papers
- Optimizing Mode Connectivity via Neuron AlignmentN. Joseph Tatro, Pin-Yu Chen, Payel Das, Igor Melnyk et al.NeurIPS 2020 · 104 citations
- Surface-Filling Curve Flows via Implicit Medial AxesYuta Noma, Silvia Sellán, Nicholas Sharp, Karan Singh et al.SIGGRAPH 2024 · 14 citations
- Learning Neural Network SubspacesMitchell Wortsman, Maxwell Horton, Carlos Guestrin, Ali Farhadi et al.ICML 2021 · 101 citations
- Revisiting Mode Connectivity in Neural Networks with Bezier SurfaceJie Ren, Pin-Yu Chen, Ren WangICLR 2025
- Loss Surface Simplexes for Mode Connecting Volumes and Fast EnsemblingGregory W. Benton, Wesley J. Maddox, Sanae Lotfi, Andrew Gordon WilsonICML 2021 · 88 citations
