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WEIGHT REDUCTION
1954
American Journal of the Medical Sciences
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One difficulty may lie in following the common practice of eating three regular meals a day and then feeling guilty about catering to an “off-beat” need for food. ...
The last is reliable and should be adopted for the evaluation of weight reduction programs; if done through- out the country, comparability of re- search results would be possible. ...
doi:10.1097/00000441-195405000-00005
fatcat:4nzjfn5jtncr5cgds27zawkisu
Dimensionality Reduction
[chapter]
2013
Image Statistics in Visual Computing
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In this paper we investigate the use of description length principles to select an appropriate number of basis functions for functional data. ...
We also explore the application of different forms of the bootstrap for functional data and use these to demonstrate the workings of our theoretical results. ...
* via (25) mimicking the data generating mechanism for X . ...
doi:10.1201/b15981-10
fatcat:k3j3buqc3jcyvn3riebnqgdmmu
Review of Dimension Reduction Methods
2021
Journal of Data Analysis and Information Processing
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The data type applied for LSA from literature search is Text data [88] [89]. ...
for some techniques, which is practically difficult to verify. ...
doi:10.4236/jdaip.2021.93013
fatcat:tlgvjk6xzbfe5gristkd7ww4tq
Mathematical Model Reduction Principle Development
2020
International Workshop on Informatics & Data-Driven Medicine
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The proposed method for the reduction of mathematical models is used for the ordinary differential equations and on the neural network model. ...
Therefore, reducing the number of parameters is an important step in data preprocessing, which is used in almost all modern systems. ...
The mechanical structure in the form of a bridge truss is in a loaded state. Perturbation of this bridge truss causes fluctuation of beams. ...
dblp:conf/iddm/MatviychukS20
fatcat:2bbsfbjqbjcflgszl7znlxi2fq
Symmetry, model reduction, and quantum mechanics
[article]
2012
arXiv
pre-print
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- together with a crisp answer to that question. Links are made to statistical models in general, to model reduction of overparametrized models and to the design of experiments. ...
Taking several statistical examples, in particular one involving a choice of experiment, as points of departure, and making symmetry assumptions, the link towards quantum theory developed in Helland (2005a ...
I am grateful to Trond Reitan for detailed comments to an earlier version of this paper. Comments on the paper by Fredrik Dahl and Anders Rygh Swensen are also acknowledged. ...
arXiv:quant-ph/0507200v2
fatcat:2rar2jogt5a5hpi3tfohtgcfbq
Dimensional Reduction in Quantum Gravity
[article]
2009
arXiv
pre-print
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The requirement that physical phenomena associated with gravitational collapse should be duly reconciled with the postulates of quantum mechanics implies that at a Planckian scale our world is not 3+1 ...
Using cellular automata as an example it is argued that this dimensional reduction implies more constraints than the freedom we have in constructing models. ...
the data in all of space-time. ...
arXiv:gr-qc/9310026v2
fatcat:g3pccfndybbjhfd3td7izh53my
Automated Reduction Of Instantaneous Flow Field Images
1985
Optical Engineering: The Journal of SPIE
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This seeding problem is compoundedby the problem of poor illumination sheet definition discussed in section 2. For the above reasons, it is not practical to assumedata on a regular grid pattern. ...
For practical use in most wind tunnel applications a larger probe area is desirable. ...
doi:10.1117/12.7973510
fatcat:rvwh7sej6vbdloprdelfovkf7a
Temporal nonlinear dimensionality reduction
2011
The 2011 International Joint Conference on Neural Networks
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It uses the additional information implicit in ordered sequences of observations to compensate for non-uniform scaling in observation space. ...
We demonstrate that TNLDR computes more accurate estimates of intrinsic state than regular NLDR, and we show that accurate estimates of state can be used to train accurate models of dynamical systems. ...
Our simple greedy path search constructs a set, B, of all the unique actions in A. ...
doi:10.1109/ijcnn.2011.6033465
dblp:conf/ijcnn/GashlerM11
fatcat:kso5q5iozzdf7obcplbzlewkvy
An effective framework for supervised dimension reduction
2014
Neurocomputing
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data when searching for a new space. ...
These effects are vital for success in practice. Such an encoding helps our framework succeed even in cases that data points reside in a nonlinear manifold, for which existing methods fail. ...
Acknowledgment We would like to thank the two anonymous reviewers for very helpful comments. Khoat Than is supported by MEXT, Japan. ...
doi:10.1016/j.neucom.2014.02.017
fatcat:pw7wiom53ben7ljmof5r2mxt44
Pattern-based behavior synthesis for FPGA resource reduction
2008
Proceedings of the 16th international ACM/SIGDA symposium on Field programmable gate arrays - FPGA '08
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Pattern-based synthesis has drawn wide interest from researchers who tried to utilize the regularity in applications for design optimizations. ...
The similarity of structures is captured by a mismatch-tolerant metric: graph edit distance. ...
Data in Table 2 also suggests a high correlation between regularities of given programs (number of patterns found) and resource reductions. ...
doi:10.1145/1344671.1344688
dblp:conf/fpga/CongJ08
fatcat:36wq4o2e2zgqznyaop6bcvejky
Asymptotics, Reduction and Emergence
2004
British Journal for the Philosophy of Science
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relationships in physics, and to provide a principled resolution to such persistent philosophical problems as multiple realisability and the nature of the special sciences. ...
All the major inter-theoretic relations of fundamental science are asymptotic ones, e.g. quantum theory as Planck's constant h ! 0, yielding (roughly) Newtonian mechanics. ...
Acknowledgements Thanks to Robert Batterman, John Collier and Ausonio Marras for frank and constructive exchanges on the difficult issues discussed here and to two anonymous journal referees for helpful ...
doi:10.1093/bjps/55.3.435
fatcat:t2kgypnvifglpg3vfzhwpi35sm
Semisupervised Dimensionality Reduction and Classification Through Virtual Label Regression
2011
IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)
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Different from previous efforts, the new approach propagates the label information from labeled to unlabeled data with a well-designed mechanism of random walks, in which outliers are effectively detected ...
and the obtained virtual labels of unlabeled data can be well encoded in a weighted regression model. ...
Unfortunately, in real cases, labeled data are usually scarce, and to label a large number of data would require expensive human labor in practice. ...
doi:10.1109/tsmcb.2010.2085433
pmid:21118781
fatcat:xkmhrofetve2jnvlp5rx4w3424
Variance Reduction in SGD by Distributed Importance Sampling
[article]
2016
arXiv
pre-print
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We propose a framework for distributing deep learning in which one set of workers search for the most informative examples in parallel while a single worker updates the model on examples selected by importance ...
We show experimentally that this method reduces gradient variance even in a context where the cost of synchronization across machines cannot be ignored, and where the factors for importance sampling are ...
ACKNOWLEDGMENTS The authors would like to acknowledge the support of the following agencies for research funding and computing support: NSERC, Calcul Québec, Compute Canada, the Canada Research Chairs ...
arXiv:1511.06481v7
fatcat:g74ajydmqjfqri7sz6ovwxfifm
Reduction and decomposition of differential automata: Theory and applications
[chapter]
1998
Lecture Notes in Computer Science
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Note: Before going to summer vacation each student will choose a project under a teacher in the department. This project will be of two semesters for III and IV. ...
Seul, "Practical Algorithms for Image Analysis: Descriptions, Examples, and Code". ...
doi:10.1007/3-540-64358-3_48
fatcat:hqwvar3zbfftdhg4cybpjwogde
Dimension reduction and variable selection in case control studies via regularized likelihood optimization
[article]
2009
arXiv
pre-print
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This extends the results of Prentice and Pyke (1979), obtained for non-regularized likelihoods. ...
We complement our theoretical results with a novel approach of determining data driven tuning parameters, based on the bisection method. ...
In Table 1 below we compared the GBM and a grid search in terms of their capability of constructing approximate regularization paths containing the true I * . ...
arXiv:0905.2171v2
fatcat:kqn2hcac7zg3re4j53dzcotxfu
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