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Sc-Lsh: An Efficient Indexing Method For Approximate Similarity Search In High Dimensional Space

Sanaa Chafik, ImaneDaoudi, Mounim A. El Yacoubi, Hamid El Ouardi
2014 Zenodo  
In order to achieve a good accuracy, a large number of hash tables is required.  ...  The Experimental results on a real large-scale dataset show that the proposed approach achieves good performances and consumes less memory than the Euclidean LSH.  ...  ACKNOWLEDGMENT We sincerely thank A. Andoni for providing us the E2LSH package.  ... 
doi:10.5281/zenodo.1094438 fatcat:cimmbqgsubbv7eulryyfhe36gm

High Dimensional Electromagnetic Interference Signal Clustering Based On SOM Neural Network

Hongyi Li, Di Zhao, Shaofeng Xu, Pidong Wang, Jiaxin Chen
2016 Electronics  
mathematical modelling of electromagnetic capability (EMC) for a large scale integrated system.  ...  To tackle with the high dimensionality of EMI signals, we combine the dimension reduction and clustering approaches, and find out the global features of different interference factors, in order to finally  ...  Existing institutions to carry out research in EMC technology can be roughly divided into two categories.  ... 
doi:10.7251/els1620027l fatcat:d5x43e2bevda5mqzpuxrbb7sku

(2021) Volume 2, Issue 4 Cultural Implications of China Pakistan Economic Corridor (CPEC Authors: Dr. Unsa Jamshed Amar Jahangir Anbrin Khawaja Abstract: This study is an attempt to highlight the cultural implication of CPEC on Pak-China relations, how it will align two nations culturally, and what steps were taken by the governments of two states to bring the people closer. After the establishment of diplomatic relations between Pakistan and China, the cultural aspect of relations between the two states al ...

2021 Journal of Development and Social Sciences  
The constitution has also empowered the existing institutions like CCI and IRSA and established several new rules for the water manageme among provinces.  ...  Inter-provincial water sharing issue in Pakistan is a classic example of upstream-downstream rivalry which has been traced back from the pre-partition history of Pakistan.  ...  Disagreement is the beauty of a relationship either between two people, two states or two provinces.  ... 
doi:10.47205/jdss.2021(2-iv)74 fatcat:o63evbbvmfghhfbrzetuczvedq

ROI Analysis Using Harvard-Oxford Atlas in Alzheimer's Disease Diagnosis Based on PCA

Hossein Dehghan
2012 Iranica Journal of Energy & Environment  
For classification of AD from NC, the proposed method achieves 89.14% of classification accuracy; while the accuracy of Automated Anatomical Labeling (AAL)-based approach is only 80.68%.  ...  In this study, an automatic method for diagnosis of AD based on region of interest (ROI) is presented.  ...  To evaluate the performance in 2003 by the National Institute on Aging (NIA), the of different classification experiments, 10-fold cross-National Institute of Biomedical Imaging and validation was performed  ... 
doi:10.5829/idosi.ijee.2012.03.03.3002 fatcat:mg4qrk3w5nglneyih5ivo3rzte

Parameter tuning is a key part of dimensionality reduction via deep variational autoencoders for single cell RNA transcriptomics [article]

Qiwen Hu, Casey S Greene
2018 bioRxiv   pre-print
Single-cell RNA sequencing (scRNA-seq) is a powerful tool to simultaneously sequencing the transcriptomes of a large number of individual cells at a high resolution.  ...  Here, we evaluate a simple VAE approach for gene expression data, Tybalt, by training and measuring its performance on sets of simulated scRNA-seq data.  ...  We performed k-means clustering for 50 times to get a stable measurement and -to evaluate a best-case scenario -we set the number of clusters, k, to the number of true cell types in the data.  ... 
doi:10.1101/385534 fatcat:uw6np4vdnvayxh7bftoametuli

An Empirical Study on Large-Scale Content-Based Image Retrieval

Yuk Man Wong, Steven C. H. Hoi, Michael R. Lyu
2007 Multimedia and Expo, 2007 IEEE International Conference on  
To the best of our knowledge, there is less comprehensive study on large-scale CBIR evaluation with a half million images.  ...  One key challenge in content-based image retrieval (CBIR) is to develop a fast solution for indexing high-dimensional image contents, which is crucial to building large-scale CBIR systems.  ...  The work described in this paper was fully supported by a grant from the Shun Hing Institute of Advanced Engineering (SHIAE), CUHK.  ... 
doi:10.1109/icme.2007.4285123 dblp:conf/icmcs/WongHL07 fatcat:dfnkxit34ndadelb7osyg7iowq

The Multidimensional Assessment of Scholarly Research Impact [article]

Henk F. Moed, Gali Halevi
2014 arXiv   pre-print
be compared one another according to their research performance.  ...  , research groups and institutions.  ...  Acknowledgement The authors wish to thank three anonymous referees for their valuable comments on an earlier version of this paper.  ... 
arXiv:1406.5520v1 fatcat:f5i57bitizdszljctpwg7nbbky

An approach based on the geometric mean of basic quantitative and qualitative bibliometric indicators to evaluate and analyse the research performance of countries and institutions [article]

Domingo Docampo, Jean-Jacques Bessoule
2019 arXiv   pre-print
We present a straightforward procedure to evaluate the scientific contribution of territories and institutions that combines the size-dependent geometric mean, Q, of the number of research documents (N  ...  Furthermore, to identify strengths and weaknesses of a given country or institution, we compute a Relative Research Output count (RROr-index) to tackle variations of the C/N ratio across research fields  ...  We are grateful to Paul Gouguet, Amélie Bernard and Pierre Madre for critical reading of the manuscript.  ... 
arXiv:1807.01049v2 fatcat:g6ku2wld2vgt5kmx3ujc45w6hy

Visualizing Very Large Graphs Using Clustering Neighborhoods [chapter]

Dunja Mladenic, Marko Grobelnik
2005 Lecture Notes in Computer Science  
This paper presents a method for visualization of large graphs in a two-dimensional space, such as a collection of Web pages.  ...  Sparse vectors have non-zero components for the vertices that are close to the vertex represented by the vector. (2) Next, we perform hierarchical clustering (eg., hierarchical K-Means) on the set of sparse  ...  ., 3, 8) are not necessary placed close to each other. Results on Two Large Graphs To show the results of the proposed approach we used two large graphs that we have constructed.  ... 
doi:10.1007/11504245_6 fatcat:jtwwm7c2hnd5fm3wgufkiiqquy

A new approach to the analysis and evaluation of the research output of countries and institutions

Domingo Docampo, Jean-Jacques Bessoule
2019 Scientometrics  
A plethora of bibliometric indicators is available nowadays to gauge research performance.  ...  Furthermore, the procedure helps to identifying strengths and weaknesses of a given country or institution, by tracking variations of performance ratios across research fields.  ...  We are grateful to Paul Gouguet, Amélie Bernard and Pierre Madre for critical reading of the manuscript. The work of D.  ... 
doi:10.1007/s11192-019-03089-w fatcat:xetbhtjnnrhmxk2e2rinzklpmq

Classification of Structural MRI Images in Alzheimer's Disease from the Perspective of Ill-Posed Problems

Ramon Casanova, Fang-Chi Hsu, Karl Herholz
2012 PLoS ONE  
In addition, to avoid the effects of the "curse of dimensionality" very often dimension reduction is applied to the data.  ...  We evaluated here the ill-posedness of this classification problem across different dimensions and sample sizes and its relationship to the performance of regularized logistic regression (RLR), linear  ...  for their thoughtful comments that helped to improve this work.  ... 
doi:10.1371/journal.pone.0044877 pmid:23071501 pmcid:PMC3468621 fatcat:76s5bivpz5cebf7yrelzwcw3ty

Evaluation of Faculty Performance of Higher Education Institution Using Principal Component Analysis

Mamatha H. K, Sridhar R, Balasubramanian S
2019 Universal Journal of Educational Research  
reducing a large number of variables into a smaller set of linear combinations (components).  ...  Principal Component analysis (PCA) is a standard statistical technique that can be used to reduce the dimensionality of a data set by assessing the dimensional structure of a dataset (Dunteman, 1989) and  ...  The two main uses of PCA are in (a) assessing the dimensional structure of a dataset [9] or (b) reducing a large number of variables into a smaller set of linear combinations (components) for subsequent  ... 
doi:10.13189/ujer.2019.071104 fatcat:ss6itmiey5ch7dkuayrfn2dneu

Embedding Learning in Hybrid Quantum-Classical Neural Networks [article]

Henry Liu, Junyu Liu, Rui Liu, Henry Makhanov, Danylo Lykov, Anuj Apte, Yuri Alexeev
2022 arXiv   pre-print
Quantum embedding learning is an important step in the application of quantum machine learning to classical data.  ...  In this paper we propose a quantum few-shot embedding learning paradigm, which learns embeddings useful for training downstream quantum machine learning tasks.  ...  This research also used the Princeton Research Computing resources at Princeton University which is consortium of groups led by the Princeton Institute for Computational Science and Engineering (PICSciE  ... 
arXiv:2204.04550v1 fatcat:otncnu5bqndkfn2cy7n4bmyz2u

m-TSNE: A Framework for Visualizing High-Dimensional Multivariate Time Series [article]

Minh Nguyen, Sanjay Purushotham, Hien To, Cyrus Shahabi
2017 arXiv   pre-print
However, such techniques might not be ideal for visualizing a large MTS dataset, since it is difficult to obtain insights or interpretations due to the inherent high dimensionality of MTS.  ...  We evaluate our visualization framework on two real-world datasets and demonstrate that the results of our m-TSNE show patterns that are easy to understand while the other methods' visualization may have  ...  Acknowledgments: This research has been funded in part by the National Cancer Institute (award number P30CA014089), National Institutes of Health, Department of Health and Human Services, under Contract  ... 
arXiv:1708.07942v1 fatcat:run3wle3hrhvvfuhglyqtgwgea

Learning Patient Representations from Text

Dmitriy Dligach, Timothy Miller
2018 Proceedings of the Seventh Joint Conference on Lexical and Computational Semantics  
We develop a neural network model for learning patient representations and show that the learned representations are general enough to obtain state-of-the-art performance on a standard comorbidity detection  ...  Mining electronic health records for patients who satisfy a set of predefined criteria is known in medical informatics as phenotyping.  ...  Acknowledgments The Titan X GPU used for this research was donated by the NVIDIA Corporation.  ... 
doi:10.18653/v1/s18-2014 dblp:conf/starsem/DligachM18 fatcat:fso4re2lerf7voeftlvnyxz3ha
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