Skip to content

Waves and Optimization Journal Club

January 28, 2021 - 3:00pm

We are starting a Journal Club for the Waves and Optimization Seminar. This club will be primarily focused on first and second year graduate students, but it is open to all grad students and postdocs who are interested in the topic and want to practice reading papers critically and giving scientific talks in a safe and supportive environment. All papers discussed will be recent (since 2017-8.) The first half of the semester will consist of group discussions, while the second half will consist of student presentations.

If you're interested in attending, we would love to have you! Whether you're a newer graduate student just getting used to reading, discussing and presenting research or a more experienced student or postdoc who has mentoring to offer, or you just have some papers to recommend, please feel free to stop by. If you're not sure whether you should drop in, then you should drop in. Our first meeting is during this coming week's Waves and Optimization Seminar, this Thursday from 3 to 4 PM, with following meetings TBD.

The paper we will be discussing this week is:

Title: Simultaneous Denoising and Interpolation of 3-D Seismic Data via Damped Data-Driven Optimal Singular Value Shrinkage
Abstract: Multichannel singular spectrum analysis (MSSA) is an effective tool for processing multidimensional time-series such as the reconstruction of high-dimensional seismic data. Low-rank estimation is a key stage in MSSA algorithm that can affect the recovery process. Truncated singular value decomposition (TSVD) and singular value thresholding (SVT) are two conventional options for rank reduction, which, however, do not result in satisfactory outcomes, especially in low signal-to-noise-ratio cases. In this letter, we propose to leverage the optimal low-rank estimator that emerges from random matrix theory known as OptShrink. The OptShrink can obtain more robust low-rank estimation in comparison with TSVD and SVT. In addition, we propose to constrain the singular values using a damping factor. The proposed damped OptShrink method is applied on real and synthetic 3-D seismic data. The comprehensive experiments and discussion verify the superior reconstruction ability of the proposed method in comparison with MSSA.



Please read through the paper before showing up if at all possible.

If you have any questions, comments or suggestions, please email me at