In this paper, we leverage the manifold structure of visual data in order to improve performance in general optimization problems subject to linear constraints.

TL;DR: It is shown that manifold constraints can be transferred from the data to the optimized variables if these are linearly correlated and the resulting ...

Manifold constraint transfer for visual structure-driven optimization · Author Picture Baochang Zhang. School of Automation Science and Electrical Engineering ...

Jan 14, 2019 · We developed Manifold, Uber's in-house model-agnostic visualization tool for ML performance diagnosis and model debugging.

This thesis deals with the setting of constrained optimization problems on manifolds and with the construction of algorithms for their numerical solution. In ...

Oct 8, 2021 · The manifold optimization framework conceptually translates a constrained optimization problem into an unconstrained optimization problem ...

We leverage the manifold structure of visual data in order to improve performance in general optimization problems subject to linear constraints.As the main ...

Missing: constraint transfer visual structure-

Manifold constraint transfer for visual structure-driven optimization, PR(77), 2018, pp. 87-98. Elsevier DOI 1802. Manifold, Transfer learning, Alternating ...

Manifold constraint transfer for visual structure-driven optimization ... In this paper we leverage the manifold structure of visual data in order to ...