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Spectral Gradient Descent Mitigates Anisotropy-Driven Misalignment: A Case Study in Phase Retrieval [PDF]
Guillaume Braun +3 more
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Gradient Descent Learning With Floats
IEEE Transactions on Cybernetics, 2022The gradient learning descent method is the main workhorse of training tasks in artificial intelligence and machine-learning research. Current theoretical studies of gradient descent only use the continuous domains, which is unreal since electronic computers use the float point numbers to store and deal with data.
Tao Sun, Ke Tang, Dongsheng Li
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2023
Large optimization problems of many variables can be difficult to solve and very computationally intensive. To dedicate greater computer resources to the problem, this thesis proposes a way to distribute the problem over many different computers using the Berkeley Open Infrastructure for Network Computing (BOINC), an open-source platform where people ...
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Large optimization problems of many variables can be difficult to solve and very computationally intensive. To dedicate greater computer resources to the problem, this thesis proposes a way to distribute the problem over many different computers using the Berkeley Open Infrastructure for Network Computing (BOINC), an open-source platform where people ...
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NOISE REDUCTION BY GRADIENT DESCENT
International Journal of Bifurcation and Chaos, 1993The problem of reducing noise in a time series from a nonlinear dynamical system can be formulated as a nonlinear minimisation process. This paper demonstrates that this can be easily solved using a steepest descent method without any of the stability problems that have been associated with using a Newton method [Hammel, 1990; Farmer & Sidorowich,
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2017
This chapter gives a broad overview and a historical context around the subject of deep learning. It also gives the reader a roadmap for navigating the book, the prerequisites, and further reading to dive deeper into the subject matter.
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This chapter gives a broad overview and a historical context around the subject of deep learning. It also gives the reader a roadmap for navigating the book, the prerequisites, and further reading to dive deeper into the subject matter.
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Hydrophilicity gradient in covalent organic frameworks for membrane distillation
Nature Materials, 2021Shuang Zhao, Jing Cun Fan, Yanhang
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