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of 47
pro vyhledávání: '"Chen, Tiancong"'
Pretrained diffusion models (DMs) have recently been popularly used in solving inverse problems (IPs). The existing methods mostly interleave iterative steps in the reverse diffusion process and iterative steps to bring the iterates closer to satisfy
Externí odkaz:
http://arxiv.org/abs/2405.16749
Recent years have seen advances in generalization bounds for noisy stochastic algorithms, especially stochastic gradient Langevin dynamics (SGLD) based on stability (Mou et al., 2018; Li et al., 2020) and information theoretic approaches (Xu and Ragi
Externí odkaz:
http://arxiv.org/abs/2201.03064
Publikováno v:
Transactions on Machine Learning Research (TMLR), 2835-8856 (12/2023)
Deep image prior (DIP) and its variants have showed remarkable potential for solving inverse problems in computer vision, without any extra training data. Practical DIP models are often substantially overparameterized. During the fitting process, the
Externí odkaz:
http://arxiv.org/abs/2112.06074
In spite of several notable efforts, explaining the generalization of deterministic non-smooth deep nets, e.g., ReLU-nets, has remained challenging. Existing approaches for deterministic non-smooth deep nets typically need to bound the Lipschitz cons
Externí odkaz:
http://arxiv.org/abs/2002.09956
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While stochastic gradient descent (SGD) and variants have been surprisingly successful for training deep nets, several aspects of the optimization dynamics and generalization are still not well understood. In this paper, we present new empirical obse
Externí odkaz:
http://arxiv.org/abs/1907.10732
Recently, there is a growing interest in the study of median-based algorithms for distributed non-convex optimization. Two prominent such algorithms include signSGD with majority vote, an effective approach for communication reduction via 1-bit compr
Externí odkaz:
http://arxiv.org/abs/1906.01736
Autor:
Jing, Li1 (AUTHOR), Chen, Tiancong1 (AUTHOR), Yang, Zhiyong2 (AUTHOR), Dong, Weiwei3 (AUTHOR) dongww@sj-hospital.org
Publikováno v:
BMC Public Health. 3/1/2024, Vol. 24 Issue 1, p1-9. 9p.
Publikováno v:
In International Journal of Electrical Power and Energy Systems February 2023 145
Akademický článek
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