Related papers: Self-Attentive Neural Collaborative Filtering
Many biological data analysis processes like Cytometry or Next Generation Sequencing (NGS) produce massive amounts of data which needs to be processed in batches for down-stream analysis. Such datasets are prone to technical variations due…
This paper has been withdrawn by the authors due to errors in the X-ray diffraction data. Other measured data are not affected; however, the errors significantly change the interpretation and conclusions, and thus warrant withdrawal and…
Recursive neural networks have widely been used by researchers to handle applications with recursively or hierarchically structured data. However, embedded control flow deep learning frameworks such as TensorFlow, Theano, Caffe2, and MXNet…
This paper has been withdrawn by the author due to an error.
This paper has been withdrawn by the authors due to a mistake in one of the proofs
This paper has been withdrawn.
Ensembles of machine learning models have been well established as a powerful method of improving performance over a single model. Traditionally, ensembling algorithms train their base learners independently or sequentially with the goal of…
Convolutional neural networks (CNNs) have demonstrated superior performance in super-resolution (SR). However, most CNN-based SR methods neglect the different importance among feature channels or fail to take full advantage of the…
This paper has been withdrawn by the authors
This paper has been withdrawn by the author due to a crucial error in the definition of homomorphism.
In NLP, convolutional neural networks (CNNs) have benefited less than recurrent neural networks (RNNs) from attention mechanisms. We hypothesize that this is because the attention in CNNs has been mainly implemented as attentive pooling…
This paper has been removed by the author due to a misstatement in Theorem 1 and a gap in its proof. A corrected and largely extended successor (a joint work with Thomas Bauer and Tomasz Szemberg) can be found under math.AG/0312211,
In recent years the need to simplify or to hide sensitive information in provenance has given way to research on provenance abstraction. In the context of scientific workflows, existing research provides techniques to semi automatically…
This paper was withdrawn by arXiv administrators upon request of the Chairperson and Spokesperson of the L3 Collaboration.
The importance of inference in Machine Learning (ML) has led to an explosive number of different proposals in ML, and particularly in Deep Learning. In an attempt to reduce the complexity of Convolutional Neural Networks, we propose a…
This paper has been withdrawn by the authors due to a mistake in the proof of Theorem 1.
This paper has been withdrawn by the author due to similarity to Author's other paper
This paper has been withdrawn by the author(s), due a crucial sign error in Thm. 11.
withdrawn by the authors because of an error.
Self-attention is a method of encoding sequences of vectors by relating these vectors to each-other based on pairwise similarities. These models have recently shown promising results for modeling discrete sequences, but they are non-trivial…