Asymptotic convergence analysis of the projection approximation subspace tracking algorithms

By Bin Yang. 1996

How researchers see this paper

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1. Liangzu Peng
2. René Vidal
3. Paris V. Giampouras
4. Yuejie Chi
5. Yue M. Lu
6. Laura Balzano
7. Ehsan Elhamifar
8. Paolo Favaro

Citations in the corpus

• The Ideal Continual Learner: An Agent That Never Forgets (2023, background): “To do so, a classic idea (e.g., see Yang (1995; 1996)) is to define a forgetting factor β with 0 β ≤ 1, and minimize the following objective in a streaming fashion: min U T∑ t=1 βT−t‖Yt −UU>Yt‖2F. (32) Here, the forgetting factor β discounts the previous samples, accounting for the fact that St is…”
• Streaming PCA and Subspace Tracking: The Missing Data Case (2018, methodology): “This approach was taken in [28], where the author used an ODE analysis to show that the PAST algorithm [25] globally converges to the target signal subspace U∗ with probability one.”