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spezial:bib [2019/12/06 13:46] laudee |
spezial:bib [2019/12/18 13:35] Zhenzhang Ye |
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award = {}, | award = {}, | ||
titleurl = {sang2020wacv.pdf}, | titleurl = {sang2020wacv.pdf}, | ||
+ | } | ||
+ | |||
+ | @article{mukkamala2019arxiv, | ||
+ | title={Bregman Proximal Framework for Deep Linear Neural Networks}, | ||
+ | author={Mahesh Chandra Mukkamala and Felix Westerkamp and Emanuel Laude and Daniel Cremers and Peter Ochs}, | ||
+ | journal = {arXiv preprint arXiv: | ||
+ | year = {2019}, | ||
+ | eprint = {1910.03638}, | ||
+ | eprinttype = {arXiv}, | ||
+ | eprintclass = {math.OC} | ||
} | } | ||
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note = { | note = { | ||
{<a href="/ | {<a href="/ | ||
+ | {<a href="/ | ||
+ | {<a href=" | ||
+ | {<a href=" | ||
}, | }, | ||
keywords={d-reconstruction, | keywords={d-reconstruction, | ||
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@article{laude2019jota, | @article{laude2019jota, | ||
title = {Bregman Proximal Mappings and Bregman-Moreau Envelopes under Relative Prox-Regularity}, | title = {Bregman Proximal Mappings and Bregman-Moreau Envelopes under Relative Prox-Regularity}, | ||
- | | + | |
- | | + | |
+ | | ||
year = {2019}, | year = {2019}, | ||
eprint = {1907.04306}, | eprint = {1907.04306}, | ||
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} | } | ||
+ | @inproceedings{brechet2019, | ||
+ | title = {Informative GANs via Structured Regularization of Optimal Transport}, | ||
+ | | ||
+ | | ||
+ | year = {2019}, | ||
+ | | ||
+ | | ||
+ | | ||
+ | } | ||