We examine the algebraic and geometric properties of a uni-directional GRU and word embeddings trained end-to-end on a text classification task. A hyperparameter search over word embedding dimension, GRU hidden dimension, and a linear combination of the GRU outputs is performed. We conclude that words naturally embed themselves in a Lie group and that RNNs form a nonlinear representation of the...

it has been proved that sphericity testing for digraphs is an np-complete problem. here, we investigate sphericity of 3-connected single source digraphs. we provide a new combinatorial characterization of sphericity and give a linear time algorithm for sphericity testing. our algorithm tests whether a 3-connected single source digraph with $n$ vertices is spherical in $o(n)$ time.

The number of published PDF documents in both the academic and commercial world has increased exponentially recent decades. There is a growing need to make their rich content discoverable information retrieval tools. Achieving high-quality semantic searches demands that document's structural components such as title, section headers, paragraphs, (nested) lists, tables figures (including caption...

In this paper, our focus is on the problems of high dimensionality and temporality. We explore deep neural network models with learned medical feature embedding to deal with these issues. Specifically, we use a multi-layer convolutional neural network (CNN) to parameterize the model and is thus able to capture complex non-linear longitudinal evolution of EHRs. Different from recent proposed dee...

Binarization is a well-known image processing task, whose objective to separate the foreground of an from background. One many tasks for which it useful that preprocessing document images in order identify relevant information, such as text or symbols. The wide variety types, alphabets, and formats makes binarization challenging. There are multiple proposals with solve this problem, classical m...

This paper presents a handwritten document recognition system based on the convolutional neural network technique. In today’s world, is rapidly attaining attention of researchers due to its promising behavior as assisting technology for visually impaired users. also helpful automatic data entry system. proposed prepared dataset English language character images. The has been trained large set s...

Legal text retrieval serves as a key component in wide range of legal processing tasks such question answering, case entailment, and statute law retrieval. The performance depends, to large extent, on the representation text, both query documents. Based good representations, model can effectively match its relevant Because documents often contain long articles only some parts are queries, it is...