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Learning Semantically Coherent and Reusable Kernels in Convolution Neural Nets for Sentence Classification
[article]
2016
arXiv
pre-print
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We demonstrate the efficacy of our core ideas of learning semantically coherent kernels and leveraging reusable kernels for efficient learning on several benchmark datasets. ...
The purpose of this work is to empirically study desirable properties such as semantic coherence, attention mechanism and reusability of CNNs in these tasks. ...
Our focus is on learning sentence classification tasks. In a sentence classification task, the goal is to predict class label information for one or more sentences. ...
arXiv:1608.00466v2
fatcat:rancvvs54fbdhai6ccyee7n5pq
Research on Action Recognition and Content Analysis in videos based on DNN and MLN
2019
Computers Materials & Continua
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First, this paper reviews the latest video action recognition methods based on Deep Neural Network and Markov Logic Network. ...
In the past few years, video action recognition, as an important direction in computer vision, has attracted many researchers and made much progress. ...
Our gratitude is extended to the anonymous reviewers for their valuable comments and professional contributions to their improvement of this paper. ...
doi:10.32604/cmc.2019.06361
fatcat:6ty3fvakize7jj5tqzcysdh4zi
Do We Really Need All Those Rich Linguistic Features? A Neural Network-Based Approach to Implicit Sense Labeling
2016
Proceedings of the CoNLL-16 shared task
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for non-explicit sense classification. ...
Despite its simplicity, our system overall outperforms all results from 2015 on 5 out of 6 evaluation sets for English and achieves an absolute improvement in F 1 -score of 3.2% on the PDTB test section ...
In order to understand how meaning is established, altered and transferred across words and sentences, a model is needed to account for contextual information as a semantically coherent representation ...
doi:10.18653/v1/k16-2005
dblp:conf/conll/SchenkCDRSR16
fatcat:hzcf2f2rjzgvnkcmjidulq6mhe
Neural Approaches to Conversational AI
[article]
2019
arXiv
pre-print
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For each category, we present a review of state-of-the-art neural approaches, draw the connection between them and traditional approaches, and discuss the progress that has been made and challenges still ...
The present paper surveys neural approaches to conversational AI that have been developed in the last few years. ...
For short sentences where information has to be inferred from the context, Lee and Dernoncourt (2016) proposed to use recurrent and convolutional neural networks that also consider texts prior to the ...
arXiv:1809.08267v3
fatcat:j57xlm4ogferdnrpfs4f2jporq
Opportunities and obstacles for deep learning in biology and medicine
2018
Journal of the Royal Society Interface
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We examine applications of deep learning to a variety of biomedical problems-patient classification, fundamental biological processes and treatment of patients-and discuss whether deep learning will be ...
Furthermore, the limited amount of labelled data for training presents problems in some domains, as do legal and privacy constraints on work with sensitive health records. ...
for clarifying edits to the abstract and introduction and Robert Gieseke, Ruibang Luo, Stephen Ra, Sourav Singh and GitHub user snikumbh for correcting typos, formatting and references. ...
doi:10.1098/rsif.2017.0387
pmid:29618526
pmcid:PMC5938574
fatcat:65o4xmp53nc6zmj37srzuht6tq
Survey of the State of the Art in Natural Language Generation: Core tasks, applications and evaluation
[article]
2018
arXiv
pre-print
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This survey therefore aims to (a) give an up-to-date synthesis of research on the core tasks in NLG and the architectures adopted in which such tasks are organised; (b) highlight a number of relatively ...
them to similar challenges faced in other areas of Natural Language Processing, with an emphasis on different evaluation methods and the relationships between them. ...
Acknowledgements We thank the four reviewers for their detailed and constructive comments. ...
arXiv:1703.09902v4
fatcat:owx2fgo2bjej3b27ve2f3ledoe
Survey of the State of the Art in Natural Language Generation: Core tasks, applications and evaluation
2018
The Journal of Artificial Intelligence Research
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challenges faced in other areas of NLP, with an emphasis on different evaluation methods and the relationships between them. ...
This survey therefore aims to (a) give an up-to-date synthesis of research on the core tasks in NLG and the architectures adopted in which such tasks are organised; (b) highlight a number of recent research ...
Acknowledgments We thank the four reviewers for their detailed and constructive comments. ...
doi:10.1613/jair.5477
fatcat:ycuteghjzncn7nx6pzkhzd6mn4
Special issue on information reuse and integration
2007
IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)
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Based on our results, we recommend using the random forest ensemble learning technique for building classification models from software measurement data, regardless of the quality and class distribution ...
Low quality or noisy data, which typically consists of erroneous values for both dependent and independent variables, has been demonstrated to have a significantly negative impact on the classification ...
The views and conclusions contained in this document are those of the authors and should not be interpreted as necessarily representing the official policies, either expressed or implied of AFRL or the ...
doi:10.1109/tsmcb.2007.912701
fatcat:xvhlaf4m3vhcdb2cicqtfrug6m
Program
2022
2022 International Conference on Decision Aid Sciences and Applications (DASA)
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The selected features from EEG recordings of 23 subjects (AD-12 and NC-11) are used to train and test the Leastsquare support vector machine (LS-SVM) classifier with three different kernel functions. ...
This process is time-consuming, biases, and subject-specific. ...
Scene Classification with Simple Machine Learning and Convolutional Neural Network Simon paper to classify the pattern of the attacks. ...
doi:10.1109/dasa54658.2022.9765271
fatcat:ttqppf4j3navnaxe653mrzmezi
28th Annual Computational Neuroscience Meeting: CNS*2019
2019
BMC Neuroscience
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We have recently revealed the presence of dynamical invariants in the pyloric CPG in the form of cycle-by-cycle linear relations among specific time intervals and the instantaneous period [4]. ...
Bio-inspired central pattern generators have been widely used to control robot locomotion, see for review [1]. ...
cortex (lmSTC) which encode semantic variables for thematic roles (such as the agent or patient in a sentence). ...
doi:10.1186/s12868-019-0538-0
fatcat:3pt5qvsh45awzbpwhqwbzrg4su
Word Sequence Modeling using Deep Learning:an End-to-end Approach and its Applications
2016
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Acknowledgements I would like to thank my advisor, Ronan Collobert for allowing me to do that thesis and Hervé Bourlard for giving me the opportunity to work at Idiap. ...
I also thank NEC and Facebook, who partially funded this thesis.
Acknowledgements ...
Neural Network Architecture Our model consists of two convolutional neural networks net e and net f as shown in Equation (3.3). ...
doi:10.5075/epfl-thesis-7204
fatcat:ahe7xyccuzc3rlfow2c6n36j5i
Spatiotemporal enabled Content-based Image Retrieval
2016
International Conference on GIScience Short Paper Proceedings
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and natural obstacles in the sensing areas (Wang and Cao 2011). ...
This is because raster representations are constrained by their spatial resolution, and their regular shapes result in redundant data for unoccupied areas. ...
Future Work Future research will extend our machine learning approach on Spark in the following four directions: (1) scanning a wider parameterization space and further optimizing search methods for the ...
doi:10.21433/b311729295dw
fatcat:fulw4pw3kfh5nmfzcsy3pkisvm
Proceedings of eNTERFACE 2015 Workshop on Intelligent Interfaces
[article]
2018
arXiv
pre-print
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During the four weeks, students and researchers from all over the world came together in the Numediart Institute of the University of Mons to work on eight selected projects structured around intelligent ...
Eight projects were selected and their reports are shown here. ...
nice schedule of social events.The authors would also thanks to Radhwan and Ambroise for their sympathy and for sharing good and bad moments with us during the workshop. ...
arXiv:1801.06349v1
fatcat:qauytivdq5axxis2xlknp3r2ne
Automating Software Development for Mobile Computing Platforms
2018
2018 IEEE International Conference on Software Maintenance and Evolution (ICSME)
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., button, dropdown menu) using a Convolutional Neural Network (CNN), and assembling these components into realistic code. ...
In this dissertation we develop techniques that aid developers in overcoming these challenges by automating and improving current software design and testing practices for mobile apps. ...
This is, in essence, an image classification task, and research on this topic has shown tremendous progress in recent years, mainly due to advancements in deep convolutional neural networks (CNNs) [186 ...
doi:10.1109/icsme.2018.00094
dblp:conf/icsm/Moran18
fatcat:idlcmxdceza67ecd7fk4llnfxm
Introduction
[chapter]
2016
Music Data Analysis
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This series aims to foster the integration between the computer sciences and statistical, numerical, and probabilistic methods by publishing a broad range of reference works, textbooks, and handbooks. ...
The interface between the computer and statistical sciences is increasing, as each discipline seeks to harness the power and resources of the other. ...
Using many hidden layers leads to deep learning (see, e.g., [1] ). Convolutional neural networks (CNNs) are a particularly successful class of deep networks. ...
doi:10.1201/9781315370996-5
fatcat:avooqogcpnbjngqmzuonil3exq
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