[PDF] Top 20 Efficient search methods for high dimensional time series
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Efficient search methods for high dimensional time series
... simulation methods is that they can only be applied to certain changepoint models that satisfy a conditional independence ...detection methods and not only Bayesian ... See full document
196
Two Distributed-State Models For Generating High-Dimensional Time Series
... promoting deep architectures is biological plausibility. Experimental evidence supports the belief that the brain uses multiple layers of feature-detecting neurons to process rich sensory input such as speech or visual ... See full document
44
An Efficient Two Step Algorithm for High Dimensional Change Point Regression Models Without Grid Search
... a high dimensional model with only a single unknown change point, whereas, Zhang et ...the high dimensional ...existing methods may be unable to satisfactorily detect the ‘no change’ ... See full document
40
Hashing Based Query Image Search using ORB Algorithm
... image search based on visual similarities has been lively topic of research in recent ...for efficient and scalable image search. Usually hashing methods are used to embed high ... See full document
9
Sparse modelling and estimation for nonstationary time series and high dimensional data
... detection methods have been proposed for time series of correlated ...the time series into dyadic blocks using binary trees, and then chose the best segmentation which minimised the ... See full document
194
Semiparametric Ultra-High Dimensional Model Averaging of Nonlinear Dynamic Time Series
... semiparametric methods to achieve dimension reduction on the candidate covariates and obtain good forecasting performance for the response ...dimension-reduction methods, is an extension of the MAMAR ... See full document
31
TSmap3D: Browser Visualization of High Dimensional Time Series Data
... alizing high dimensional time series data in 3D space as a sequence of 3D point ...highly efficient parallel implementation of Multidimensional Scaling (MDS) [1] for mapping high ... See full document
10
Nonlinear time series: semiparametric and nonparametric methods
... nonlinear time series data. Models and methods used have been based initially on parametric non- linear or nonparametric time series ...related methods may be too restrictive in ... See full document
245
Multi-dimensional Time Series Approximation Using Local Features at Thinned-out Keypoints
... other methods. Suppose two long multi-dimensional time series are given and A-LTK is used to calculate the similarity between the ...of time series for comparison, will be ... See full document
11
Search for Additive Nonlinear Time Series Causal Models
... nonlinear time series causal ...linear time series to the simulated ...available efficient automated causal inference algorithm for linear time series with contemporaneous ... See full document
25
ENSEMBLE METHODS FOR TIME SERIES CLASSIFICATION
... decade, time series similarity search has been given a great deal of attention by data mining ...many time series representations and distance measures have been ...on time ... See full document
12
Machine Learning Methods with Time Series Dependence
... of methods which have been proposed for sequential data. Since these methods have been applied with success to a variety of tasks such as part-of-speech tagging, text-to-speech mapping, biological sequence ... See full document
231
Factor modeling for high dimensional time series
... functional time series has been of a more theoretical nature; see ...inference methods focus mostly on nonparametric estimation of some characteristics of functional series (Part IV of Ferraty ... See full document
90
A Literature Survey on Query Adaptive Image Search using Hash Code
... image search based on visual similarities has been lively topic of research in recent ...for efficient and scalable image search. Usually hashing methods are used to embed high ... See full document
5
Spectral analysis of high dimensional time series
... in high-dimensional statistical inference, in contrast with classical ones, is the fixed-sample ...for high dimensions, a common practice is to exploit concentration inequalities, then to provide ... See full document
24
Essays in high dimensional nonlinear time series analysis
... return time series are determined using linear ...statistical methods, that extract the unobservable or latent factors directly from the portfolios of return time series, are factor ... See full document
155
Efficient protein structure search using indexing methods
... to search, and Δr is the amount of value added to r after each iteration, and C is used to obtain key value for index ...processing time and evaluation ratio as Δ r ... See full document
15
MapReduce based Method for User Friendly XML Keyword Search
... friendly methods for XML searching is LCA/ELCA ...keyword search is that it is not a fast ...MLCA search techniques, Fuzzy type-ahead searching and so ... See full document
8
Simulation based methods for time series diagnostics
... T he approxim ation in (3.52) has a negligible effect on th e posterior d istribution obtained for th e size of th e intervention variable. Consider an in sta n t t = t'. Suppose th ere is n ot an outlier a t t = t', and ... See full document
197
Bayesian Methods for High-dimensional Data.
... model-based methods, which fit a parameterized model to the entire rating matrix, and then make predictions based on the learned ...Related methods can be found in Breese et ...developed methods ... See full document
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