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Contrastive analysis for scatterplot-based representations of dimensionality reduction
(2021-01-01)
Cluster interpretation after dimensionality reduction (DR) is a ubiquitous part of exploring multidimensional datasets. DR results are frequently represented by scatterplots, where spatial proximity encodes similarity among ...
How optimizing perplexity can affect the dimensionality reduction on word embeddings visualization?
(Springer, 2019-12-01)
Traditional word embeddings approaches, such as bag-of-words models, tackles the problem of text data representation by linking words in a document to a binary vector, marking their occurrence or not. Additionally, a term ...
Supersymmetric soliton solution in a dimensionally reduced schrödinger-chern-simons model
(American Physical Society, 2011-02)
We obtain, by dimensional reduction, a (1+1) supersymmetric system introduced in the description of ultracold quantum gases. The correct supercharges are identified and their algebra is constructed. Finally, novel solitonic ...
Comments on ‘Two-dimensional slope stability analysis by limit equilibrium and strength reduction methods'
(2008)
This article presents comments to the document 'Two-dimensional slope stability analysis by limit equilibrium and strength reduction methods'
A dimension reduction scheme for the computation of optimal unions of subspaces
(Sampling Publishing, 2011-11)
Given a set of points F in a high dimensional space, the problem of finding a union of subspaces U_i V_i ⊆ R^N that best explains the data F increases dramatically with the dimension of R^N. In this article, we study a ...
Relations between two-dimensional models from dimensional reduction
(1998-12-15)
In this work we explore the consequences of dimensional reduction of the 3D Maxwell-Chern-Simons and some related models. A connection between topological mass generation in 3D and mass generation according to the Schwinger ...
Boosted projections and low cost transfer learning applied to smart surveillance
(Universidade Federal de Minas GeraisUFMG, 2018-02-23)
Computer vision is an important area related to understanding the world through images. It can be used in biometrics, by verifying whether a given face is of a certain identity, used to look for crime perpetrators in an ...
Forecasting conditional covariance matrices in high-dimensional time series: a general dynamic factor approach
(2019-06)
Based on a General Dynamic Factor Model with infinite-dimensional factor space, we develop a new estimation and forecasting procedures for conditional covariance matrices in high-dimensional time series. The performance ...