Learning of the detection task
Different Absorption from the Same Sharing: Sifted Multi task Learning for Fake News Detection
... specific task to weight shared features for paying more attention to helpful ...specific task and the shared features of both ...news detection task, and key matrix K shared and value matrix V ...
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Multi-task deep learning from Sentinel-1 SAR: ship detection, classification and length estimation
... Ship detection cannot be totally assessed, but a visual inspection still shows our network achieved good ...the detection task but jointly deliver relevant performance for ship classification (above ...
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Overview of the ImageCLEFmed 2019 Concept Detection Task
... concept detection task. The latest deep learning system ResNet-101 was used for a multi-label classification approach, as well as a CNN-RNN model framework with attention ...
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Overview of the ImageCLEFmed 2019 concept detection task
... The training and validation sets containing 56,629 and 14,157 images were subsets of the ROCO data set presented in Peltka et al. [11]. ROCO has two classes: Radiology and Out-Of-Class. The first contains 81,825 ...
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Multi-task learning with mutual learning for joint sentiment classification and topic detection
... Mutual Learning for Joint Sentiment Classification and Topic Detection Lin Gui, Jia Leng, Jiyun Zhou, Ruifeng Xu, Yulan He Abstract—Recently, advances in neural network approaches have achieved many ...
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MITRE at SemEval 2016 Task 6: Transfer Learning for Stance Detection
... sure how an author’s opinion is expressed in sponta- neous, unstructured messages rather than the explicit prompts of formal opinion polls. Declarations of stance are often couched in fig- urative language that can be ...
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Automatic Multi-task Learning System for Abnormal Network Traffic Detection
... the detection of abnormal network traf- ...machine learning meth- ods are adopted to solve this learning ...deep learning methods. Deep learning provides the potential for end- to-end ...
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Rumor Detection by Exploiting User Credibility Information, Attention and Multi task Learning
... the task description paper already pointed out: the overall inter-annotator agreement rate of ...the task to be challenging, and easier for source tweets ...
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Emotion Detection and Classification in a Multigenre Corpus with Joint Multi Task Deep Learning
... Abstract Detection and classification of emotion categories expressed by a sentence is a challenging task, due to subjectivity of ...separate task, we use soft parameter shared layers across the ...
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RIDDL at SemEval 2018 Task 1: Rage Intensity Detection with Deep Learning
... formance, task specific hyper-parameter optimiza- tion could be employed, which is shown in strat- egy 2 where tuning the number of epochs on a per task basis helps the ...
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THU NGN at SemEval 2018 Task 3: Tweet Irony Detection with Densely connected LSTM and Multi task Learning
... Dense-LSTM model; 6) Dense-LSTM+ens, us- ing our Dense-LSTM model and ensemble strat- egy. In addition, we apply multi-task learning technique to all models except the benchmark sys- tem based on SVM. The ...
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EmoDet at SemEval 2019 Task 3: Emotion Detection in Text using Deep Learning
... 1 Introduction The past decades have seen an explosive growth of user-generated content through social media platforms. People are expressing online their feelings and opinions on a variety of topics on a daily basis. ...
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MITRE at SemEval 2019 Task 5: Transfer Learning for Multilingual Hate Speech Detection
... SemEval-2019 Task 5, HatEval: Multilin- gual detection of hate speech against immi- grants and women in ...transfer learning from auxiliary tasks, including a novel method for adapting pre- trained ...
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Binarizer at SemEval 2018 Task 3: Parsing dependency and deep learning for irony detection
... our side during submission the results are based on 446 out of 784 instances in the test data. The models perform better than the baseline system as per the competition leaderboard. This reinforces the notion that ...
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Amobee at SemEval 2017 Task 4: Deep Learning System for Sentiment Detection on Twitter
... We started with the training data passing our pipeline. We calculated the mean distribution for each entity on the training and testing datasets. We trained a logistic regression from a 5-label to a binary distribution ...
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JUSTDeep at NLP4IF 2019 Task 1: Propaganda Detection using Ensemble Deep Learning Models
... 6 Conclusion In this paper, we have investigated several models and techniques to detect if a sentence in an article is propaganda or not. Experimental results showed that the ensemble of using BiLSTM, XGBoost, and BERT ...
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Killing Four Birds with Two Stones: Multi Task Learning for Non Literal Language Detection
... the detection problem as a generalized non-literal language classification ...multi- task learning for related non-literal language ...multi-task learning consistently improves upon ...
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IIT Gandhinagar at SemEval 2019 Task 3: Contextual Emotion Detection Using Deep Learning
... Gujarat, India {arik.pamnani,rajat.goel,choudhari.jayesh,singh.mayank}@iitgn.ac.in Abstract Recent advancements in Internet and Mobile infrastructure have resulted in the development of faster and efficient platforms of ...
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Dick Preston and Morbo at SemEval 2019 Task 4: Transfer Learning for Hyperpartisan News Detection
... slanted learning rates and number of training epochs have been used for the different submitted FOI classi- fiers, but we have in general found learning rates around ...
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HITS SBD at the FinSBD Task: Machine Learning vs Rule based Sentence Boundary Detection
... 6 Summary and Conclusion We presented two competing systems for SBD that were de- veloped for the Fin-SBD shared task 2019. The ML-based system was based on a simple and elegant approach which was inspired by the ...
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