@conference {dasilva2015WSLRigt,
	title = {Irregular grid tensor completion},
	booktitle = {Workshop on Low-rank Optimization and Applications},
	year = {2015},
	note = {(Workshop on Low-rank Optimization and Applications, University of Bonn, Germany)},
	month = {06},
	abstract = {Low rank tensor completion has recently garnered the attention of researchers owing to the ubiquity of tensors in the sciences and the theoretical and numerical challenges compared to matrix completion. Here we consider a tensor completion scheme where the data arises from sampling a continuous function. When the sampling grid is not periodic, the resulting tensor may not be low rank in the Hierarchical Tucker sense, which can adversely affect reconstruction quality when there are missing samples. In order to compensate for this off-grid sampling, we introduce a resampling operator (here, the non-uniform Fourier transform) that accounts for this non-uniformity moreso than merely treating the sampling grid as periodic. Numerical experiments demonstrate that this approach can improve reconstruction quality when there is relatively little data.},
	keywords = {hierarchical tucker, irregular sampling, off the grid, structured tensor, tensor interpolation},
	presentation = {https://slim.gatech.edu/Publications/Public/Conferences/WS_LR/2015/dasilva2015WSLRigt/dasilva2015WSLRigt_poster.pdf},
	author = {Curt Da Silva and Felix J. Herrmann}
}
@conference {dasilva2015EAGEogt,
	title = {Off the grid tensor completion for seismic data interpolation},
	booktitle = {EAGE Annual Conference Proceedings},
	year = {2015},
	note = {(EAGE, Madrid)},
	month = {06},
	abstract = {The practical realities of acquiring seismic data in a realistic survey are often at odds with the stringent requirements of Shannon-Nyquist-based sampling theory. The unpredictable movement of the ocean{\textquoteleft}s currents can be detrimental in acquiring exactly equally-spaced samples while sampling at Nyquist-rates are expensive, given the huge dimensionality and size of the data volume. Recent work in matrix and tensor completion for seismic data interpolation aim to alleviate such stringent Nyquist-based sampling requirements but are fundamentally posed on a regularly-spaced grid. In this work, we extend our previous results in using the so-called Hierarchical Tucker (HT) tensor format for recovering seismic data to the irregularly sampled case. We introduce an interpolation operator that resamples our tensor from a regular grid (in which we impose our low-rank constraints) to our irregular sampling grid. Our framework is very flexible and efficient, depending primarily on the computational costs of this operator. We demonstrate the superiority of this approach on a realistic BG data set compared to using low-rank tensor methods that merely use binning.},
	keywords = {EAGE, hierarchical tucker, irregular sampling, off the grid, structured tensor, tensor interpolation},
	doi = {10.3997/2214-4609.201412978},
	url = {https://slim.gatech.edu/Publications/Public/Conferences/EAGE/2015/dasilva2015EAGEogt/dasilva2015EAGEogt.html},
	presentation = {https://slim.gatech.edu/Publications/Public/Conferences/EAGE/2015/dasilva2015EAGEogt/dasilva2015EAGEogt_pres.pdf},
	author = {Curt Da Silva and Felix J. Herrmann}
}
