Papers Data Visualization
“Data Visualization” 태그가 달린 논문 335편 · 필터 해제
Optimizing the Information Retrieval Trade-off in Data Visualization Using $\alpha$-Divergence
Data visualization is one of the major applications of nonlinear dimensionality reduction. From the information retrieval perspective, the quality of a visualization can be evaluated by considering the extent that the ne…
Data VisualizationDimensionality ReductionInformation RetrievalRetrievalVisualizations Relevant to The User By Multi-View Latent Variable Factorization
A main goal of data visualization is to find, from among all the available alternatives, mappings to the 2D/3D display which are relevant to the user. Assuming user interaction data, or other auxiliary data about the ite…
Data VisualizationShapeNet: An Information-Rich 3D Model Repository
We present ShapeNet: a richly-annotated, large-scale repository of shapes represented by 3D CAD models of objects. ShapeNet contains 3D models from a multitude of semantic categories and organizes them under the WordNet …
Data VisualizationmodelAdversarial Autoencoders
In this paper, we propose the "adversarial autoencoder" (AAE), which is a probabilistic autoencoder that uses the recently proposed generative adversarial networks (GAN) to perform variational inference by matching the a…
ClusteringData VisualizationDecoderDimensionality Reduction+4Dimension Reduction with Non-degrading Generalization
Visualizing high dimensional data by projecting them into two or three dimensional space is one of the most effective ways to intuitively understand the data's underlying characteristics, for example their class neighbor…
Data VisualizationDimensionality ReductionGeneral ClassificationVMF-SNE: Embedding for Spherical Data
T-SNE is a well-known approach to embedding high-dimensional data and has been widely used in data visualization. The basic assumption of t-SNE is that the data are non-constrained in the Euclidean space and the local pr…
Data VisualizationRandom Maxout Features
In this paper, we propose and study random maxout features, which are constructed by first projecting the input data onto sets of randomly generated vectors with Gaussian elements, and then outputing the maximum projecti…
Data VisualizationDimensionality ReductionGeneral ClassificationGeneralization BoundsMaximum Entropy Linear Manifold for Learning Discriminative Low-dimensional Representation
Representation learning is currently a very hot topic in modern machine learning, mostly due to the great success of the deep learning methods. In particular low-dimensional representation which discriminates classes can…
Data VisualizationDimensionality ReductionGeneral ClassificationRepresentation LearningCiting on-line Language Resources
Although the possibility of referring or citing on-line data from publications is seen at least theoretically as an important means to provide immediate testable proof or simple illustration of a line of reasoning, the p…
Data VisualizationTranslog-II: a Program for Recording User Activity Data for Empirical Reading and Writing Research
This paper presents a novel implementation of Translog-II. Translog-II is a Windows-oriented program to record and study reading and writing processes on a computer. In our research, it is an instrument to acquire object…
Data VisualizationMachine TranslationTranslationANALEC: a New Tool for the Dynamic Annotation of Textual Data
We introduce ANALEC, a tool which aim is to bring together corpus annotation, visualization and query management. Our main idea is to provide a unified and dynamic way of annotating textual data. ANALEC allows researcher…
Data VisualizationManagementtext annotationPAMOCAT: Automatic retrieval of specified postures
In order to understand and model the non-verbal communicative conduct of humans, it seems fruitful to combine qualitative methods (Conversation Analysis) and quantitative techniques (motion capturing). A Tools for data v…
Data VisualizationMotion SegmentationRetrievalTime Series AnalysisHow to Evaluate Dimensionality Reduction? - Improving the Co-ranking Matrix
The growing number of dimensionality reduction methods available for data visualization has recently inspired the development of quality assessment measures, in order to evaluate the resulting low-dimensional representat…
Data VisualizationDimensionality ReductionHeavy-Tailed Symmetric Stochastic Neighbor Embedding
Stochastic Neighbor Embedding (SNE) has shown to be quite promising for data visualization. Currently, the most popular implementation, t-SNE, is restricted to a particular Student t-distribution as its embedding distri…
Data VisualizationPrincipal Manifolds and Nonlinear Dimension Reduction via Local Tangent Space Alignment
Nonlinear manifold learning from unorganized data points is a very challenging unsupervised learning and data visualization problem with a great variety of applications. In this paper we present a new algorithm for manif…
Data VisualizationDimensionality Reduction