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- 9 KB (1,544 words) - 19:30, 31 May 2024
- ...polymorphisms (SNPs), insertions, and deletions (indels). Calling SNPs and small indels are technically challenging since it requires a program to distingui This paper aims to solve the problem of calling SNPs and small indels using a convolutional neural net by casting the reads as images and ...18 KB (2,856 words) - 04:24, 16 December 2020
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- \small W(p_r, p_g) = \underset{\gamma\sim\Pi(p_r, p_g)} {\inf}\pmb{\mathbb{E}}_{(x ...)</math>, and corresponding densities with lower case letters, i.e. <math>\small p(x)</math>. ...21 KB (3,416 words) - 22:25, 25 April 2018
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- ...intrinsic dimension of the data. Since <math>\hat{n}</math> could be very small compared to the dimension <math>n</math> of the data, this algorithm is com Since <math> \beta </math> is very small, and we want to avoid large value of <math> z </math>, we could change vari ...7 KB (1,209 words) - 09:46, 30 August 2017
- ...ction that is mainly focused on modeling large dissimilarities rather than small ones. As a result of that, they do not provide good visualizations of data ...l the entropy of <math> \mathbf{ P_i} </math> is within some predetermined small tolerance of <math> \mathbf{\log_2 M } </math>. ...15 KB (2,530 words) - 09:45, 30 August 2017
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- So, we can take some small number of samples <math>y</math>, compute the sparse representation <math>s ...ty is now clear: when a signal has a sparse expansion, one can discard the small coefficients without much perceptual loss. Formally, consider <math>f_{S}(t ...13 KB (2,258 words) - 09:45, 30 August 2017
- In this study, NN LMs are trained only on a small part of the data (which are in-domain corpora) plus some randomly subsample performance for small values of M, and even with M = 2000, ...9 KB (1,542 words) - 09:46, 30 August 2017
- |Week of Nov 25 || Yuliang Shi || || Small-gan: Speeding up gan training using core-sets || [http://proceedings.mlr.pr ...5 KB (642 words) - 23:29, 1 December 2021
- ...adding more convolutional layers, which is feasible due to the use of very small (3 × 3) convolution filters in all layers. As a result, they come up with s ...d through a stack of convolutional (conv.) layers with filters with a very small receptive field: 3 × 3 with a convolutional stride of 1 pixel. Spatial poo ...11 KB (1,680 words) - 09:46, 30 August 2017
- ...-art Gaussian Mixture Models-Hidden Markov Model (GMM-HMM) systems in both small and large speech recognition tasks ...lores using multiple convolutional layers, and the system is tested on one small dataset and two large datasets. The results show that CNNs outperform DNNs ...11 KB (1,587 words) - 09:46, 30 August 2017
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- ...><br>Optimizing your Google Business Profile (GBP) If you're an owner of a small business that would like to increase your local visibility, it should be on ...9 KB (1,582 words) - 06:14, 27 May 2024