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Representing Objects, Relations, and Sequences
[article]
2015
arXiv
pre-print
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With respect to machine learning, for some types of problems appropriate VSA representations permit us to prove learnability, rather than relying on simulations. ...
Vector Symbolic Architectures (VSAs) are high-dimensional vector representations of objects (eg., words, image parts), relations (eg., sentence structures), and sequences for use with machine learning ...
Self-Organizing maps present another possibility
[Kohonen 1995, Hagenbuchner et al. 2009]. ...
arXiv:1501.07627v1
fatcat:bqi44i6jjzhs5lgc6bo3fvw254
An amorphous model for morphological processing in visual comprehension based on naive discriminative learning
2011
Psychological review
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Frequency effects for complex words as well as for phrases (Arnon & Snider, 2010 ) emerge in the model without the presence of whole-word or whole-phrase representations. ...
The model also replicates the finding of Plag and Baayen (2009) , that, on average, words with more productive affixes elicit longer response latencies, while at the same time predicting that productive ...
For instance, the number of n-gram types on which our model was trained, 1,496,103, represents only a fraction of the number of n-grams occurring in the bnc alone. ...
doi:10.1037/a0023851
pmid:21744979
fatcat:oeqi2hmnxvfqjmn5sl45mr5yei
Toward Integrated Large-Scale Environmental Monitoring Using WSN/UAV/Crowdsensing: A Review of Applications, Signal Processing, and Future Perspectives
2022
Sensors
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By outlining the available solutions and current limitations, we identify in the cooperation among terrestrial (WSN/crowdsensing) and aerial (UAVs) sensing, coupled with the adoption of advanced signal ...
Fighting Earth's degradation and safeguarding the environment are subjects of topical interest and sources of hot debate in today's society. ...
Acknowledgments: The author would like to thank Angelo Coluccia for the insightful discussions on the topic and the extensive review of the paper. ...
doi:10.3390/s22051824
pmid:35270970
pmcid:PMC8914857
fatcat:xqcgx676mbckfpc2a6rurbfooq
Optimized Biosignals Processing Algorithms for New Designs of Human Machine Interfaces on Parallel Ultra-Low Power Architectures
2020
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This is followed by several case studies in the biomedical field, starting with the analysis of a Hand Gesture Recognition, based on the Hyperdimensional Computing algorithm, which allows performing a ...
The last part is dedicated to an exploration of typical modules for the development of optimized ECG-based applications. ...
Moreover, sensitivity and specificity define the quality of the classification for model validation: S ensitivity = T P T P + FN (3.3) S peci f icity = T N FP + T N (3.4)
Hyperdimensional Computing ...
doi:10.6092/unibo/amsdottorato/9381
fatcat:kjpnbovoszbdvaipuakhzouzf4
Improving Automated Literature-based Discovery with Neural Networks: Neural biomedical Named Entity Recognition, Link Prediction and Discovery
2019
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To be capable of solving these problems, automated LBD needs to accurately glean the extensive information present in literature, cope with the dynamic nature of scientific knowledge and place high-quality ...
Recent advances in Natural Language Processing (NLP) allow for deep textual analysis to obtain a wide coverage of information present in text and can adapt easily to recognising new biomedical entities ...
I thank the members of the 11 Roseford Road community who I was lucky to share it with: Ulrich, Theresia, Jess, Patrick, Talia, Mark, Blaise and Ronja. ...
doi:10.17863/cam.40995
fatcat:cxbq3gxnnjcotdytstxtx3w26u