2024
Local Distance Correlation Embedding for Time-Series Analysis on Riemannian Manifolds
Lincon S. Souza, Takumi Kobayashi, Yasunori Nishimori, Yasuko Sugase-Miyamoto, Kenji Kawano, Shotaro Akaho +1
ICASSP 2024accepted
This paper proposes a time-series data embedding technique that preserves curvature and orientation, with a focus on visualizing temporal manifold-valued data. Manifold-valued data provide pair-wise local distances on which the proposed method is built. First, we introduce a simpler form of our meth…