This repository contains code of manifold embedded knowledge transfer (MEKT). MEKT is a novel transfer learning framework for offline unsupervised cross-subject electroencephalogram (EEG) classification. It can cope with variations among different individuals and/or tasks in unsupervised scenarios, and has...
Manifold Embedded Knowledge Transfer for Brain-Computer Interfacesdoi:10.1109/TNSRE.2020.2985996Wen ZhangDongrui WuIEEEInternational Conference of the IEEE Engineering in Medicine and Biology Society
As differentiable manifolds, embedded in ℝN as well as abstract, became better understood, in particular under the influence of H. Whitney, it was not difficult to obtain a C∞-structure, unique but for equivalence on any C1-manifold: C∞↔C1is bijective. Manifolds being “slippery” ...
3.3 Riemannian MCMC in embedded space The coordinate expressions of these dynamics allow straightforward simulation in the coordinate space, as if in the usual Euclidean space. However, this may also be problematic in some cases. When the manifold does not have a global coordinate system, such as...
ManifoldEmbeddedDistributionAlignment (MEDA) method to address the challenges of both degenerated feature transfor- mation and unevaluated distribution alignment. MEDA learns a domain-invariant classi er in Grassmann manifold with struc- tural risk minimization, while performing dynamic distribution alignment ...
Qualitatively, the solution manifold .M covers too many independent directions to be embedded in a low-dimensional subspace. To address this issue, several techniques have been developed: • Problem-specific methods tackle the difficulties of some specific physics problems that are known to be non...
The recovery of these post-training context-specific networks is an improvement over previous work, which requires that the context is embedded into the model pre-training. SupirFactor is therefore a valuable tool to identify context specific and contextual regulatory interactions. The driving features...
- Knowledge-Based Systems 被引量: 0发表: 2023年 FAULT DIAGNOSIS METHOD BASED ON ADAPTIVE MANIFOLD EMBEDDED DYNAMIC DISTRIBUTION ALIGNMENT A fault diagnosis method based on adaptive manifold embedded dynamic distribution alignment. The optimal subspace dimension is automatically calculated, an... C Shen,...
As differentiable manifolds, embedded in ℝN as well as abstract, became better understood, in particular under the influence of H. Whitney, it was not difficult to obtain a C∞-structure, unique but for equivalence on any C1-manifold: C∞↔C1is bijective. Manifolds being “slippery” ...
In this study, the authors proposed a manifold embedded distribution adaptation (MDA) approach to narrow the distribution gap in manifold feature subspace. MDA maps source and target project data to manifold subspace and then joint distribution adaptation of conditional and marginal ...