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05/05/2022
Uncertainty-Based Non-Parametric Active Peak Detection
Active, non-parametric peak detection is considered. As a use case, acti...
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06/14/2020
Fast Robust Subspace Tracking via PCA in Sparse Data-Dependent Noise
This work studies the robust subspace tracking (ST) problem. Robust ST c...
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02/28/2020
Federated Over-the-Air Subspace Learning from Incomplete Data
Federated learning refers to a distributed learning scenario in which us...
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02/13/2019
Phaseless Low Rank Matrix Recovery and Subspace Tracking
This work introduces the first simple and provably correct solution for ...
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10/06/2018
Subspace Tracking from Missing and Outlier Corrupted Data
We study the related problems of subspace tracking in the presence of mi...
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03/01/2018
Static and Dynamic Robust PCA via Low-Rank + Sparse Matrix Decomposition: A Review
Principal Components Analysis (PCA) is one of the most widely used dimen...
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12/17/2017
MEDRoP: Memory-Efficient Dynamic Robust PCA
Robust PCA (RPCA) is the problem of separating a given data matrix into ...
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11/26/2017
Robust PCA and Robust Subspace Tracking
Principal Components Analysis (PCA) is one of the most widely used dimen...
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09/19/2017
Finite Sample Guarantees for PCA in Non-Isotropic and Data-Dependent Noise
This work obtains novel finite sample guarantees for Principal Component...
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05/24/2017
Provable Dynamic Robust PCA or Robust Subspace Tracking
Dynamic robust PCA refers to the dynamic (time-varying) extension of the...
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02/10/2017
