[PDF] Top 20 Gated Multi Task Network for Text Classification
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Gated Multi Task Network for Text Classification
... Multi-task model with deeper layers shared can augment deeper knowledge and greatly increase the feature space (Zhang et al., 2017). But unde- sirable interference inevitably and simultaneously comes with ... See full document
6
Automatic Detection and Classification of Argument Components using Multi task Deep Neural Network
... Naive Bayes, Random Forest and SVM (Support Vector Machine). (Park and Cardie, 2014) also used a SVM to determine the extent to which claims are justified in citizen’s comments related to possible new legislation ... See full document
9
Multi Dimensional Text Classification
... Category is a powerful tool to manage a large number of text documents. By grouping text documents into a set of categories, it is possible for us to efficiently keep or search for information we need. At ... See full document
7
Falcon: A Novel Chinese Short Text Classification Method
... Dense connection. Densely connected networks proposed by Dr. Huang Gao [5] [6] consist of multiple dense blocks, each of which consists of multiple layers. Each layer produces k features, where ( K ) is referred to as ... See full document
11
Continual and Multi Task Architecture Search
... image classification and language ...for text classification and video caption generation tasks and their integra- tion to two transfer learning paradigms of contin- ual learning and ... See full document
12
Document Modeling with Gated Recurrent Neural Network for Sentiment Classification
... sentiment classification re- mains a significant challenge: how to encode the intrinsic (semantic or syntactic) relations between sentences in the semantic meaning of documen- ...sentiment classification ... See full document
11
Multimodal Emoji Prediction
... the text associated to it and only one ...(2017)). Task: We extend the experimental scheme of Bar- bieri et ...a classification task: given an image or a text (or both inputs in the ... See full document
8
Multinomial Adversarial Networks for Multi Domain Text Classification
... method, ASP-MTL (Liu et al., 2017). ASP-MTL is the first empirical attempt to use a multinomial adversarial network for multi-task learning, but is more restricted and can be viewed as a special case ... See full document
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Initializing neural networks for hierarchical multi label text classification
... input text, where the la- bels are a part of a hierarchical structure (such as a ...(OVR) classification setup, where a binary clas- sifier is trained for each label in the tax- onomy or ontology where all ... See full document
9
Representation Learning Using Multi Task Deep Neural Networks for Semantic Classification and Information Retrieval
... single task, ...of multi-task learning (Caruana, 1997), we propose in this paper a multi-task DNN approach for representation learning that leverages supervised data from many ...of ... See full document
10
Exploring Human-Like Reading Strategy for Abstractive Text Summarization
... neural network based methods, generating plausible and high-quality abstractive summaries remains a challenging ...abstractive text summariza- tion, which however is able to improve the effectiveness of the ... See full document
8
Text Level Graph Neural Network for Text Classification
... ing text classification (Defferrard et ...Neural Network (GCN) in text classifica- tion task and outperformed the traditional CNN ...state-of-the-art text clas- sification ... See full document
7
Multi Task Learning of Keyphrase Boundary Classification
... boundary classification (KBC) is the task of detecting keyphrases in sci- entific articles and labelling them with re- spect to predefined ...this task is so far un- derexplored, partly due to the ... See full document
6
Concept Classification with Bayesian Multi task Learning
... Strikingly, very similar regions were picked by the classifier for the other two category pairs with high classification accuracy, i.e., building-kitchen and buildpart-tool. This fact brings back the issue about ... See full document
8
An Interactive Multi Task Learning Network for End to End Aspect Based Sentiment Analysis
... Aspect-Based Sentiment Analysis. Existing ap- proaches typically decompose ABSA into two subtasks, and solve them in a pipeline setting. Both AE (Qiu et al., 2011; Yin et al., 2016; Wang et al., 2016a, 2017; Li and Lam, ... See full document
12
Multi Task Label Embedding for Text Classification
... labor-intensive. Multi-Task Learn- ing (MTL) solves this problem by jointly train- ing multiple related tasks and leveraging poten- tial correlations among them to increase corpora size implicitly, extract ... See full document
9
Cluster Gated Convolutional Neural Network for Short Text Classification
... short text classification, but the performance of such methods is strongly dependent on the quality of knowledge bases and constructing a large-scale knowledge base is time- consuming and ... See full document
10
Multi level Gated Recurrent Neural Network for dialog act classification
... Using the deep learning framework, researchers have developed various systems to deal with DA and related problems like sentiment analysis and sentence classification. One can build a simple CNN architecture like ... See full document
10
Hierarchical deep neural networks for MeSH subject prediction
... tasks[34][33], multi-label classification tasks[29][6][28], and extreme classification tasks[38][41] to great ...separate task from the prediction of the more specific and less frequent ... See full document
44
MCapsNet: Capsule Network for Text with Multi Task Learning
... for text classification under the scheme of ...single-task network enhanced by capsules is already a strong ...with multi- ple kernel sizes further improves the performance and get best ... See full document
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