A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
Filters
From Feature To Paradigm: Deep Learning In Machine Translation
2018
The Journal of Artificial Intelligence Research
Preserved Fulltext
Integration of deep learning in MT varies from re-modeling existing features into standard statistical systems to the development of a new architecture. ...
Finally, we include an analysis of the corresponding challenges and future work in using deep learning in MT. ...
This manuscript presents an overview from the early stages of how deep learning has started as a feature function in statistical MT (Schwenk, Costa-Jussà, & Fonollosa, 2006) to become an entire new paradigm ...
doi:10.1613/jair.1.11198
fatcat:zk7tszi4dfboxmeg2vfm2xbtje
From Feature to Paradigm: Deep Learning in Machine Translation (Extended Abstract)
2018
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
Integration of deep learning in MT varies from re-modeling existing features into standard statistical systems to the development of a new architecture. ...
The specific field of Machine Translation (MT) has not remained invariant. ...
Acknowledgements The authors would like to specially thank Prof. Kobi Gal for his invitation to participate in the IJCAI journal track. ...
doi:10.24963/ijcai.2018/789
dblp:conf/ijcai/Costa-Jussa18
fatcat:uwapnqtfive3zn4wbfnqmuvcbe
Curriculum Learning and Minibatch Bucketing in Neural Machine Translation
2017
RANLP 2017 - Recent Advances in Natural Language Processing Meet Deep Learning
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf.
We examine the effects of particular orderings of sentence pairs on the on-line training of neural machine translation (NMT). ...
"curriculum learning"). ...
Multidisciplinarity to Interdisciplinarity. ...
doi:10.26615/978-954-452-049-6_050
dblp:conf/ranlp/KocmiB17
fatcat:3432tnq73zezvpzkymhdwcmhqe
Persian–Spanish Low-Resource Statistical Machine Translation Through English as Pivot Language
2017
RANLP 2017 - Recent Advances in Natural Language Processing Meet Deep Learning
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf.
Machine Translation (SMT). ...
Finally we suggest a method called combination model in which the standard direct model and the best triangulation pivoting model are blended in order to reach a high-quality translation. ...
The authors have benefited from her erudition and thoughtful comments which truly enriched the present work. ...
doi:10.26615/978-954-452-049-6_004
dblp:conf/ranlp/AhmadniaSH17
fatcat:ugrtyxbksnhwlhflj3lcjegqw4
Feature Extraction for Hyperspectral Imagery: The Evolution from Shallow to Deep
[article]
2020
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Other Versions
The advances in feature extraction have been inspired by two fields of research, including the popularization of image and signal processing as well as machine (deep) learning, leading to two types of ...
In more detail, this paper provides a bird's eye view over shallow (both supervised and unsupervised) and deep feature extraction approaches specifically dedicated to the topic of hyperspectral feature ...
ACKNOWLEDGMENT The authors would like to thank Prof. ...
arXiv:2003.02822v2
fatcat:2l37q46y6ndqjooo6pkcqezmzi
Image Matching from Handcrafted to Deep Features: A Survey
2020
International Journal of Computer Vision
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Following the feature-based image matching pipeline, we first introduce feature detection, description, and matching techniques from handcrafted methods to trainable ones and provide an analysis of the ...
Over the past decades, growing amount and diversity of methods have been proposed for image matching, particularly with the development of deep learning techniques over the recent years. ...
Classical Learning-Based Detectors Early from the past decade, classical learning-based methods, such as decision tree, support vector machine (SVM), and other classifiers by opposition to Deep Learning ...
doi:10.1007/s11263-020-01359-2
fatcat:a2epfaolwjfm5mcrsmn7g6sd7m
Deep Learning Training and Benchmarks for Earth Observation Images: Data Sets, Features, and Procedures
[chapter]
2020
Recent Trends in Artificial Neural Networks - from Training to Prediction
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Therefore, we need reliably labeled data sets and tools to train the developed algorithms and to assess the performance of our deep learning paradigms. ...
Deep learning methods are often used for image classification or local object segmentation. ...
Acknowledgements We appreciate the cooperation with Politehnica University of Bucharest (UPB) in Romania and our project partners from the European H2020 projects CANDELA (under grant agreement No. 776193 ...
doi:10.5772/intechopen.90910
fatcat:ajwyldahcvggnfwax7ecl6wx4u
Network Representation Learning: From Preprocessing, Feature Extraction to Node Embedding
[article]
2021
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
This survey not only helps researchers and practitioners to gain an in-depth understanding of different network representation learning techniques but also provides practical guidelines for designing and ...
Over dozens of network representation learning algorithms have been reported in the literature. ...
Different from traditional feature engineering that relies heavily on handcrafted statistics to extract structural information, NRL introduces a new data-driven deep learning paradigm to capture, encode ...
arXiv:2110.07582v1
fatcat:gbjn3evwwzf4xkeobrsfo6hope
Deep Learning Paradigm with Transformed Monolingual Word Embeddings for Multilingual Sentiment Analysis
[article]
2017
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
Other Versions
However, this paradigm is conditioned by the quality of machine translation. In this paper, we propose a new deep learning paradigm to assimilate the differences between languages for MSA. ...
So far, traditional methods resorted to machine translation---translating texts in other languages to English, and then adopt the methods once worked in English. ...
In this paper, we proposed a novel deep learning paradigm for MSA. ...
arXiv:1710.03203v2
fatcat:2uwd5egwlfg5tp76ypwggw4z5i
Network Representation Learning: From Traditional Feature Learning to Deep Learning
2020
IEEE Access
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
INTRODUCTION R EPRESENTATION learning is a new paradigm in the machine learning field aiming at representing information efficiently. ...
In this survey, we try to go through the development of data representation in graphstructured data from TFL to recent NRL based on deep learning. ...
doi:10.1109/access.2020.3037118
fatcat:kca6htfarjdjpmtwcvbsppfzui
Python as Multi Paradigm Programming Language
2020
International Journal of Computer Applications
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
Like IoT Applications, Machine Learning, Deep Learning, Artificial Intelligence, Cyber Security, etc. ...
This Paper will also include various characteristics and features of python proving why it is the widely used programming language in recent times. ...
Python for Machine Learning & Deep Learning AI, Machine Learning and Deep Learning are the future, and are the topics that are at a boom these days, and as is Python. ...
doi:10.5120/ijca2020919775
fatcat:kpyncdxxarbblocbpib6bcap6m
Transferring ConvNet Features from Passive to Active Robot Self-Localization: The Use of Ego-Centric and World-Centric Views
[article]
2022
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
In our framework, the ILC and OLC are mapped to a state vector and subsequently used to train a multiview NBV planner via deep reinforcement learning. ...
Specifically, we divide the visual cues that are available from the CNN model into two types: the output layer cue (OLC) and intermediate layer cue (ILC). ...
Although most existing active VPR methods are non-deep, in recent years, attempts have been made to boost active VPR using deep learning. ...
arXiv:2204.10497v1
fatcat:uofb3ikgz5bqnga2623uxiy4gm
Video Coding for Machines: A Paradigm of Collaborative Compression and Intelligent Analytics
[article]
2020
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Other Versions
The recent endeavors in imminent trends of video compression, e.g. deep learning based coding tools and end-to-end image/video coding, and MPEG-7 compact feature descriptor standards, i.e. ...
In this paper, thanks to booming AI technology, e.g. prediction and generation models, we carry out exploration in the new area, Video Coding for Machines (VCM), arising from the emerging MPEG standardization ...
As illustrated in Fig. 2 , VCM attempts to connect the features of different granularities to the human/machine vision tasks from the perspective of a general deep learning framework. ...
arXiv:2001.03569v2
fatcat:22dsiwby6nfrbicoxyk2ufwhjy
Paradigm shift in electron-based crystallography via machine learning
[article]
2019
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
Electron backscatter diffraction patterns are collected from materials with well-known crystal structures, then a deep neural network model is constructed for classification to a specific Bravais lattice ...
This paper presents a newly developed methodology that represents a paradigm change in electron diffraction-based structure analysis techniques, with the potential to revolutionize multiple crystallography-related ...
Other discovered features might be obvious to experts, but difficult to translate into specific logic. ...
arXiv:1902.03682v1
fatcat:ytqneqfm4nf3rov4b6wossqpoe
Machine Teaching: A New Paradigm for Building Machine Learning Systems
[article]
2017
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
Other Versions
The current processes for building machine learning systems require practitioners with deep knowledge of machine learning. ...
We believe that in order to meet this growing demand for machine learning systems we must significantly increase the number of individuals that can teach machines. ...
Acknowledgements We thank Jason Williams for his support and contributions to Machine Teaching. ...
arXiv:1707.06742v3
fatcat:4btdbfgwkvhdtpantomqlxs4qy
« Previous
Showing results 1 — 15 out of 46,374 results