Essays about: "Regularization"
Showing result 26 - 30 of 143 essays containing the word Regularization.
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26. Topology optimization: perimeter restriction using total variation
University essay from Lunds universitet/Hållfasthetslära; Lunds universitet/Institutionen för byggvetenskaperAbstract : Topology optimization is a method used to find optimal material distributions, within a specified domain, with respect to some performance measure. To avoid various artifacts to appear in the suggested design, the solution space is typically restricted, where some restriction methods allow different length scales to be controlled in the design. READ MORE
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27. Investigating Relations between Regularization and Weight Initialization in Artificial Neural Networks
University essay from Lunds universitet/Beräkningsbiologi och biologisk fysik - Genomgår omorganisationAbstract : L2 regularization is a common method used to prevent overtraining in artificial neural networks. However, an issue with this method is that the regularization strength has to be properly adjusted for it to work as intended. This value is usually found by trial and error which can take some time, especially for larger networks. READ MORE
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28. Predicting misuse of subscription tranquilizers : A comparasion of regularized logistic regression, Adaptive Bossting and support vector machines
University essay from Uppsala universitet/Statistiska institutionenAbstract : Tranquilizer misuse is a behavior associated with substance use disorder. As of now there is only one published article that includes a predictive model on misuse of subscription tranquilizers. READ MORE
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29. Distance preserving Fermat VAE
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Deep neural networks takes their strength in the representations, or features, that they internally build. While these internal encodings help networks performing classification or regression tasks on specific data types, it exists a branch of machine learning that has for only purpose to build these representations. READ MORE
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30. Towards topology-aware Variational Auto-Encoders : from InvMap-VAE to Witness Simplicial VAE
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Variational Auto-Encoders (VAEs) are one of the most famous deep generative models. After showing that standard VAEs may not preserve the topology, that is the shape of the data, between the input and the latent space, we tried to modify them so that the topology is preserved. READ MORE