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...the previous sections, alternatively updating G and D requires significant attention. We modify the way we update the generator G to improve stability and gener ...

This idea is also successfully used in attention networks[13] such as image captioning and machine translation. In this pape ...o, K., Courville, A., and Bengio, Y. Describing multi- media content using attention-based Encoder–Decoder networks. IEEE Transactions on Multimedia, 17(11): 18 ...

...oped in the literature. The latter sub-task has received relatively little attention and is typically borrowed without justification from the PCA context. In th ...

...ls which can do few-shot estimations of data. This can be implemented with attention mechanisms (Reed et al., 2017) or additional memory units in a VAE model ( ...their case features of samples are compared with target features using an attention kernel. At a higher level one can interpret this model as a CNP where the a ...

...ng generative adversarial networks[8], variational autoencoders (VAE)[17], attention models[18], have shown that a deep network can learn an image distribution ...

Attention-based models: #Bahdanau et al. (2014): These are a different class of models which use attention modules(different architectures) to help focus the neural network to decide ...

...red solution in image recognition and computer vision problems, increasing attention has been dedicated to evolving the network architecture to further improve ...

field has attracted the attention of a wide research community, which resulted in ...

Neural network first caught people’s attention during the 2012 imageNet contest. A solution using neural network achieve 8 ...

Independent component analysis has been given more attention recently. It is become a popular method for estimating the independent feat ...

...calculated using BERT, Roberta, XLNET, and XLM models, which utilize self-attention and nonlinear transformations. ...

...ieval can potentially improve QA system performance, and has received more attention. ...

...uivalently, to the description logic ALCQ, which has received considerable attention in the knowledge representation community (Baader et al., 2003; Baader & Lu ...

...it, Llion Jones, Aidan N Gomez, Lukasz Kaiser, and Illia Polosukhin. 2017. Attention is all you need. In Advances in Neural Information Processing Systems, page ...

...n approaches for solving machine learning problems have gained significant attention. In this paper, the non-convex boosting in classification using integer pro ...

...ts are fixed to need only 1-bit precision, it is now possible to focus our attention on the features preceding it. ...szkoreit, Llion Jones, Aidan N Gomez, Lukasz Kaiser, and Illia Polosukhin. Attention is all you need. 2017. ...

...911 calls: victims trapped in a tall building who seek immediate medical attention, locating emergency personnel such as firefighters or paramedics, or a mino ...

...ining parameters still needs to be clarified. In addition, it is worthy of attention and further explanation about the results of prediction accuracy, under wha ...

* Gregor et al. (2015) used a recurrent variational autoencoder with attention mechanisms for reading and writing different portions of the image canvas. ...

Now we turn our attention back to the the problem of measuring independence between two (generally mu ...

...a result, data-intensive promotional strategies are getting more and more attention nowadays from marketing teams to further improve company returns. ...

...zkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, and Illia Polosukhin. Attention is all you need. CoRR, abs/1706.03762, 2017. ...

...use of algorithms for finding optimal DNN architectures has attracted the attention of researchers who have tackled the problem through four main groups of tec ...

* At the beginning, the study mentions that the pooling method is not under attention as it should be. In the end, results show that choosing the pooling method ...

...to be an unaccounted component of tuning the model but this receives scant attention in the current paper. Several numerical comparisons should be carried out t ...

...erent image sets and backend cloud services. Also, by taking a look at the attention maps for some of the images, we will figure out why the agent has chosen th ...

...ory prediction algorithms using other machine learning algorithms, such as attention-aware neural networks. ...

...ization is a key issue that has recently attracted a significant amount of attention in a wide range of applications. Navigation, vehicle tracking, Emergency Ca ...

From the above code, we should pay attention to the following aspects when comparing with SVD method: ...ki/Vapnik Vapnik], Chervonenkis et al., however the ideas did not gain any attention until strong results were shown in the early 1990s. ...

...so when we need to determine <math>\!x_{t+1}</math>, we only need to pay attention in <math>\!x_{t}</math>. ...

...e started in the late seventies (Vapnik, 1979), it is receiving increasing attention recently by researchers. It is such a powerful method that in the few years ...ssified points are given higher weight to ensure the classifier "pays more attention" to them, to fit better in the next iteration. The idea behind boosting is ...

...ferent function altogether, such as a <math>\,sin(x)</math> dimension. Pay attention, We don't do QDA with LDA. If we try QDA directly on this problem the resul SVM was introduced after neural networks and gathered attention by outperforming neural networks in many applications e.g. bioinformatics, ...

Attention:There is a "dot" between sqrt(d) and "*". It is because d and tet are vecto ...