high-dimensional space
Fast and secure similarity search in high dimensional space
... I. I NTRODUCTION Quickly identifying in a very large database the elements that are the most similar to a given query is a central need for many applications. While this has been solved many years ago for traditional ...
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Mixture of markov trees for bayesian network structure learning with small datasets in high dimensional space
... to high dimensional spaces with hundreds of variables and can identify a structure with higher score in less time than the Sparse Candidate ...of high dimensional space (thousands of ...
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Anderson Localization in high dimensional lattices
... Fock space of Slater determinants, which plays the role of lattice sites in a disordered one-particle Anderson tight-binding ...finite dimensional lattice is thus interpreted as a one-particle localization ...
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High-dimensional $p$-norms
... a high-dimensional space tends to be meaning- less for norms with larger exponents, since the maximum observed distance tends towards the minimum ...
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Null-controllability of linear hyperbolic systems in one dimensional space
... This paper is devoted to the controllability of a general linear hyperbolic system in one space dimension using boundary controls on one side. Under precise and generic assumptions on the boundary conditions on ...
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Cliques in high-dimensional random geometric graphs
... show a rather high tendency for clustering (my ‘friends’ are connected with high prob- ability). Is it true that in the opposite case G(n, p, d) and G(n, p) resemble each other? We believe in the conjecture ...
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Cliques in high-dimensional random geometric graphs
... Cliques in high-dimensional RGGs 9 graphs G(n, p, d) and G(n, p) are practically identical. In this case it looks quite reasonable to try to get a result about small distance between the two random models ...
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Automated high-dimensional flow cytometric data analysis
... resulting high-dimensional data and have led to growing interest and recent activity in the development of new computa- tional tools and approaches ...
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Design space exploration in high-level synthesis
... As done by other related works (e.g. [64][36] [71][86][114][138][36]), I have evaluated the quality of the performed explorations in terms ADRS. Parameter tuning In Section 5.2.1, I introduced a tuneable parameter r ma x ...
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Similarity Learning for High-Dimensional Sparse Data
... low-dimensional space (using PCA or random projections), and then learn a similar- ity function in the reduced ...feature space, when we are interested in discov- ering what features are more ...
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Model selection for sparse high-dimensional learning
... Let us give an example using the MNIST data set which contains 70.000 images of hand- written digits with ten classes (from 0 to 9). Fitting a traditional Gaussian mixture or using k-means leads to wrongly classifying ...
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Kernel methods for high dimensional data analysis
... the space: the minimum λ such that every ball can be covered by λ balls of half the radius, and corresponds to the doubling dimension of X, defined as dim(X) = log 2 ...metric space can be embedded in a ...
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Cosmic Evolution from Phase Transition of Three-Dimensional Flat Space
... flat space boundary conditions [ 9 , 10 ], and (iii) the solutions do not have conical ...flat space solutions imply that there are leading terms in the metric that can fluctuate like the g tt ...
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High-dimensional intracity quantum cryptography with structured photons
... implement high-dimensional protocols in order to improve noise resistance and increase the data ...of high-dimensional QKD in the single- photon regime has been conducted outside of the ...a ...
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Biologically inspired incremental learning for high-dimensional spaces
... the high-dimensional input space by grid distances in the projected input space (the hidden layer of our architecture) which is a key property of the SOM algorithm we employ for this ...
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Two-dimensional phase cartography for high-harmonic spectroscopy
... to high- resolution HHS for quantum orbital tomography or attosecond charge migration studies in ...with high precision; this dipole can then be used to perform a quantum orbital reconstruction with ...
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Doubly-robust evaluation of high-dimensional surrogate markers
... When evaluating the effectiveness of a treatment, policy, or intervention, the desired measure of effectiveness may be expensive to collect, not routinely available, or may take a long time to occur. In these cases, it ...
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Group lasso estimation of high-dimensional covariance matrices
... Keywords: Group Lasso; ℓ 1 penalty; high-dimensional covariance estimation; basis expansion; sparsity; oracle inequality; sparse PCA. Subject Class. MSC-2000 : 62G05, 62H25 Acknowledgments: this work was ...
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The PLATO Simulator: modelling of high-precision high-cadence space-based imaging
... DAK06) and five events cm −2 s −1 for Kepler (NASA 2009). Such impacts can leave their marks with a large range of e ffects and shapes on the detector surface. They can saturate a single pixel or produce a streak of ...
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Cognitive conflict in learning three-dimensional space station structures
... actual space stations in order to learn their ...complete space station ...another-- space station architectures are generally not designed with consistent visual verticals between the different ...
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