local hidden variable
A Physical Basis for Entanglement in a Non Local Hidden Variable Theory
... and hidden-variable ...non-local hidden-variable (NLHV) design for particles, and does not yet have a mathe- matical ...a hidden-variable theory could ...
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Algorithmic Construction of Local Hidden Variable Models for Entangled Quantum States
... “ local ” entangled states — can be perfectly reproduced using a local hidden variable (LHV) model, ...constructed local hidden state models (LHS), a special class of LHV model ...
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Energy Conversion Mechanics for Photon Emission per Non Local Hidden Variable Theory
... the hidden- variable ...all local hidden-variable designs and some classes of non-local designs ...non-local hidden-variable (NLHV) designs have not been ...
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Better local hidden variable models for two-qubit Werner states and an upper bound on the Grothendieck constant $K_G(3)$
... many) local measurements? For pure entangled states, the answer turns out to be positive [ 3 ...a local hidden vari- able (LHV) model for any possible local project- ive ...
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Entropy at the Level of Individual Particles: Analysis of Maxwell’s Agent with a Hidden Variable Theory
... Problem: Maxwell’s Agent (MA) is a thought experiment about whether the second Law is violated at smaller scales. This is a complex problem because the scale dependencies are unclear for per- fect gas assumptions, ...
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Entity Decisions in Neural Language Modelling: Approaches and Problems
... We explore different approaches to explicit en- tity modelling in language models (LM). We independently replicate two existing models in a controlled setup, introduce a simplified vari- ant of one of the models and ...
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Noisy-OR Component Analysis and its Application to Link Analysis
... latent variable model that as- sumes the expression of observed high-dimensional binary data is driven by a small number of hidden binary sources combined via noisy-or ...
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Electricity consumption probability density forecasting method based on LASSO-Quantile Regression Neural Network
... Motivated by the existing research, we propose a new learning method to predict electricity consumption, which combines LASSO and QRNN. The details will be given in the next section. LASSO can produce high- quality ...
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AGui Based Hybrid Clustering Technique for Brain Tumor Segmentation and Validation in Mri Images
... operation of K means in that EM starts with an initial estimate for the missing variable and iterates to find the maximum likelihood (ML) for these variables. Unlike K-means, in EM the numbers of clusters that are ...
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Development of a computational framework for protein homology detection by incorporating realignment
... (2006) MUMMALS: Multiple Sequence Alignment Improved by using Hidden Markov Models with Local Structural Information, Nucleic Acids Research.. and Grishin, N.V.[r] ...
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Robust Lossless Semi Fragile Information Protection in Images
... Table 2 shows the embedding capacity of proposed approach against classical approach using difference expansion. We compared our method with the Tian’s approach [33] because it is a benchmark and widely adopted for ...
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Combating The Obesogenic Environment: Helping Children Hold Onto Health
... and local prevalence of overweight, some of which indicate eating and exercise behaviors, con- sumption of hidden calories, and ethnicity, there can be no doubt that the prevalence of obesity in chil- dren ...
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Sentence Simplification for Semantic Role Labeling
... Compared to previous SRL models, our model has several qualitative advantages. First, we be- lieve that the simplification process, which repre- sents the syntax as a set of local syntactic transfor- mations, is ...
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Generalising the Discriminative Restricted Boltzmann Machine
... its hidden units models the {0, 1}- Bernoulli ...their hidden units, this has not been attempted with the ...containing hidden units with the Binomial and {−1, +1}-Bernoulli distributions ...
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Exploring Application Level Semantic for Data Compression
... compressing big data sets. Instead of compression over basic data units, the compression was conducted over partitioned data chunks. The MapReduce programming model was adopted for the algorithms implementation to ...
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Variable bandwidth local maximum likelihood type estimation for diffusion processes
... However, local linear regression methods are very sensitive to outliers, and individual outliers can lead to large changes in the results of statistical inference, therefore lead- ing to irrational and even ...
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Community-based HIV prevention research among substance-using women in survival sex work: The Maka Project Partnership
... a local sex work agency to examine the HIV-related vulnerabilities, barriers to accessing care, and impact of current prevention and harm reduction strategies among women in survival sex ...
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Gibbs Max-margin Topic Models with Data Augmentation
... latent variable models has received increasing attention because of the promise of using latent variables to capture the underly- ing structures of the complex ...the hidden structures by using some ...
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Single cell transcriptomics unveils gene regulatory network plasticity
... Single-cell sequencing is characterized by a series of technical limitations that generate artifacts, such as drop-out events, irregular sequencing depth, and low li- brary complexity. First, drop-out events represent ...
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Local Regularization of Noisy Point Clouds: Improved Global Geometric Estimates and Data Analysis
... of local regularization in classification ...tractable local-regularization depends on a parameter that modulates the amount of localization, and our analysis suggests the appropriate scaling of said ...
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