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study processes. interacting the Coupling in stochastic technique of a is theoretical widely used
Coupling is a widely used technique in the theoretical study of interacting stochastic processes.
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"lifted techniques inference" Numerous proposed. have been such for approaches
Numerous approaches for such "lifted inference" techniques have been proposed.
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We to separate amplification two decomposition the W a Schur use of mechanisms.
We use a Schur decomposition of W to separate the two amplification mechanisms.
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weak. must limited that find We be slowing dynamical if is amplification very kept
We find that amplification is very limited if dynamical slowing must be kept weak.
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samples. random consider from set learning a problem of the We
We consider the problem of learning a set from random samples.
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challenging, IRP solution is of even metaheuristics. for the biobjective The rather
The solution of the biobjective IRP is rather challenging, even for metaheuristics.
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profound effective neighborhood structures. representations lacking are solution appropriate a of understanding We and still
We are still lacking a profound understanding of appropriate solution representations and effective neighborhood structures.
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understanding of work the contributes such solution Our representations. to better
Our work contributes to the better understanding of such solution representations.
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margins are dimensionality reduction controlled weight Generalization, maximizing minimizing and vectors. by the
Generalization, dimensionality reduction and maximizing the margins are controlled by minimizing weight vectors.
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multimodal show good biometric by proposed paper. pattern this system in Results
Results show good pattern by multimodal biometric system proposed in this paper.
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discussed. by large maximum inference sample are likelihood estimation for and Furthermore,
Furthermore, estimation by maximum likelihood and inference for large sample are discussed.
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for We an clustering. Carlo Monte based hierarchical coalescent Bayesian new sampler sequential present
We present an new sequential Monte Carlo sampler for coalescent based Bayesian hierarchical clustering.
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modeling Our non-i.i.d. model appropriate is for
Our model is appropriate for modeling non-i.i.d.
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on data closely and show Results real approaches. artificial related over significant improvements
Results on artificial and real data show significant improvements over closely related approaches.
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data in proteomics, contains correlation complicated genomics, High-dimensional often common chemometrics structures. and
High-dimensional data common in genomics, proteomics, and chemometrics often contains complicated correlation structures.
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the point period of At oscillations bifurcation the the diverges.
At the bifurcation point the period of the oscillations diverges.
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of disposes datasets geographic Today, of large of composed one's thousands objects.
Today, one's disposes of large datasets composed of thousands of geographic objects.
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this In necessary. methods robust context, become sampling
In this context, robust sampling methods become necessary.
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on method this we techniques. propose paper, In sampling clustering based a
In this paper, we propose a sampling method based on clustering techniques.
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method shows select that objects. to our allows of samples This case-study relevant
This case-study shows that our method allows to select relevant samples of objects.
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the standard In supervised learning, data is the only labeled observed.
In the standard supervised learning, only the labeled data is observed.
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as are supervised problems The formalized learning. regression the classification and
The classification and regression problems are formalized as the supervised learning.
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labeled data. unlabeled semi-supervised obtained In to addition also learning, in data is
In semi-supervised learning, unlabeled data is also obtained in addition to labeled data.
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is in unlabeled to learning. improve exploiting data semi-supervised accuracy prediction Hence, the important
Hence, exploiting unlabeled data is important to improve the prediction accuracy in semi-supervised learning.
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problems missing estimation problem with as is This data. regarded semiparametric a
This problems is regarded as a semiparametric estimation problem with missing data.
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usefulness of present experiments methods. our Some the numerical
Some numerical experiments present the usefulness of our methods.
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In priors. a propose novel this for sparsity-inducing the of construction framework paper we
In this paper we propose a novel framework for the construction of sparsity-inducing priors.
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sparse can nonconvex framework with mixtures a Furthermore, penalization. Bayesian subserve Laplace scale for learning
Furthermore, Laplace scale mixtures can subserve a Bayesian framework for sparse learning with nonconvex penalization.
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can be of densities EP-GIG explicitly expressed. The
The densities of EP-GIG can be explicitly expressed.
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distribution posterior distribution. corresponding the inverse Moreover, generalized follows a also Gaussian
Moreover, the corresponding posterior distribution also follows a generalized inverse Gaussian distribution.
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learning. algorithms for These sparse EM us lead properties Bayesian to
These properties lead us to EM algorithms for Bayesian sparse learning.
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extensions selection present grouped regression. variable two addition, we and In for logistic
In addition, we present two extensions for grouped variable selection and logistic regression.
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mathematical age-old among "justification" cliche an for marriage provides This a counselors.
This provides a mathematical "justification" for an age-old cliche among marriage counselors.
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Both methods use problem error humans frequently systems artificial trial to and and solving.
Both humans and artificial systems frequently use trial and error methods to problem solving.
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perfect. control knowledge Unfortunately, is rarely this
Unfortunately, this control knowledge is rarely perfect.
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is artificial difficult. in often in one's of own knowledge systems-as Moreover, humans-self-evaluation
Moreover, in artificial systems-as in humans-self-evaluation of one's own knowledge is often difficult.
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our of have been Thus the using approach encouraging. results far,
Thus far, the results of using our approach have been encouraging.
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the on repository. an Our available is package R algorithm as CRAN
Our algorithm is available as an R package on the CRAN repository.
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we method In represent head a for novel paper, pose estimation. this
In this paper, we represent a novel method for head pose estimation.
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transform use the for we efficiency estimation feature the To enhance of extraction. contourlet
To enhance the efficiency of the estimation we use contourlet transform for feature extraction.
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Then, apply as neighborhood classifiers different we distance. minimum (knn) k-nearest such and
Then, we apply different classifiers such as k-nearest neighborhood (knn) and minimum distance.
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available to database evaluate use of proposed the We FERET performance the public method.
We use the public available FERET database to evaluate the performance of proposed method.
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of results Simulation robustness method. the the superior proposed indicate
Simulation results indicate the superior robustness of the proposed method.
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In problems defines clearly occurs Paper, CFA the authors the the this image. in
In this Paper, the authors clearly defines the problems occurs in the CFA image.
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a rate, which vaccine evolution high Influenza challenging. design has makes
Influenza has a high evolution rate, which makes vaccine design challenging.
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dominant approach detection an here We new of early strains. for consider
We here consider an approach for early detection of new dominant strains.
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dominant define strains. We emergence of metric detect then the a to
We then define a metric to detect the emergence of dominant strains.
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annual appear strain detection tool vaccine influenza useful would for be to selection. This
This strain detection tool would appear to be useful for annual influenza vaccine selection.
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discuss biological modularity hierarchy In and review, systems. we in this
In this review, we discuss modularity and hierarchy in biological systems.
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will Experimental reviewed. this support for be description
Experimental support for this description will be reviewed.
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networks. will be and networks, metabolic Examples networks, from protein-protein interaction pathogen presented gene structure,
Examples will be presented from pathogen structure, metabolic networks, gene networks, and protein-protein interaction networks.
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networks. will Additional pathways, social networks, and presented physiology, developmental be ecological from examples food
Additional examples will be presented from ecological food networks, developmental pathways, physiology, and social networks.
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under can model solved some The assumptions. be analytically simplest
The simplest model can be solved analytically under some assumptions.
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the examples. in two model of demonstrate the utility We
We demonstrate the utility of the model in two examples.
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We sequence-based to effectiveness in here introduce vaccine humans. a method predict
We here introduce a sequence-based method to predict vaccine effectiveness in humans.
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with cell the B probability The rate. hypermutation $p$ decreases
The probability $p$ decreases with the B cell hypermutation rate.
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output by The final obtained is interpolation.
The final output is obtained by interpolation.
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the to classroom A illustrate presented experiment in also results is practice. of our use
A classroom experiment is also presented to illustrate the use of our results in practice.
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then of Post-processing moving is to used the boundaries refine objects.
Post-processing is then used to refine the boundaries of moving objects.
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but of large fitness populations consider landscapes. finite on evolution We arbitrary the
We consider the evolution of large but finite populations on arbitrary fitness landscapes.
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describe Markov, Moran process. a process evolutionary We by the
We describe the evolutionary process by a Markov, Moran process.
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This enantioselectivity. question puts into key-lock models for
This puts into question key-lock models for enantioselectivity.
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from human tracking dataset. I show Eva on We pose results widely-used Human the also
We also show results on tracking human pose from the widely-used Human Eva I dataset.
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to evolves to system antibodies Influenza it. escape that immune from bind virus
Influenza virus evolves to escape from immune system antibodies that bind to it.
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A with constant. substitution positive G$ $\Delta\Delta value decreases the binding antibody
A substitution with positive $\Delta\Delta G$ value decreases the antibody binding constant.
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$\Delta\Delta On charged G$ the average acid amino an uncharged highest generates to substitution values.
On average an uncharged to charged amino acid substitution generates the highest $\Delta\Delta G$ values.
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Also generate on average, zero. near acids amino between $\Delta\Delta values small substitutions G$ to
Also on average, substitutions between small amino acids generate $\Delta\Delta G$ values near to zero.
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view. this of simulations Carlo support to virus are evolution Monte presented
Monte Carlo simulations of virus evolution are presented to support this view.
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model mutation individual-based under Evolutionary analysed population is stochastic, in a branching selection. and
Evolutionary branching is analysed in a stochastic, individual-based population model under mutation and selection.
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studied in the mutational dynamics evolutionary Then, of the limit step is traditionally, sizes. vanishing
Then, traditionally, the evolutionary dynamics is studied in the limit of vanishing mutational step sizes.
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non-negligible approach, the small mutational present steps but are In considered.
In the present approach, small but non-negligible mutational steps are considered.
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it ancient in nature. and suggests Evidence is ubiquitous both
Evidence suggests it is both ancient and ubiquitous in nature.
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phenomenon, consensus and unifying the importance of the principles lacking. appear Despite
Despite the importance of the phenomenon, consensus and unifying principles appear lacking.
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biological of integration. path neural representation is the for needed A issue fundamental space
A fundamental issue is the neural representation of space needed for biological path integration.
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is type of allothetic directional also available idiothetic, The namely or cue, considered.
The type of available directional cue, namely allothetic or idiothetic, is also considered.
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animals, and navigation Efficient planning for path transportation. robotics, is and logistics critical
Efficient path planning and navigation is critical for animals, robotics, logistics and transportation.
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connectivity. spiking wave propagates network, activity synaptic a hippocampus-like of the through altering A
A wave of spiking activity propagates through a hippocampus-like network, altering the synaptic connectivity.
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autocatalytic results This of from study of presents a paper new detailed sets. structure the
This paper presents new results from a detailed study of the structure of autocatalytic sets.
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quantitative examination This applicable analysis of the method to BSCs. is of quantitative
This quantitative method of examination is applicable to the quantitative analysis of BSCs.
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the with single click infinite and about finite formula We the time give potential.
We give the formula about the single click time with finite and infinite potential.
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provide results new understanding potential. a infinite These of
These results provide a new understanding of infinite potential.
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the states the whole unadaptive parameters adaptive and We regimes. analytically for demonstrate
We analytically demonstrate the adaptive and unadaptive states for the whole parameters regimes.
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about with parameters regions the points is issues Interesting fixed imaginary demonstrated. the
Interesting issues about the parameters regions with the imaginary fixed points is demonstrated.
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graphical results framework to quantitative a phenomenon. the These suggest study and absorbing
These results suggest a graphical and quantitative framework to study the absorbing phenomenon.
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performance method the We our with of examples. illustrate
We illustrate the performance of our method with examples.
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applications decade. The face its reliability in using proved last biometric has
The applications using face biometric has proved its reliability in last decade.
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DWT using (DBC- DBC Recognition propose FR) Face paper, In based model. this we
In this paper, we propose DBC based Face Recognition using DWT (DBC- FR) model.
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algorithm. render compared better existing proposed to recognition percentage rate algorithm The the
The proposed algorithm render better percentage recognition rate compared to the existing algorithm.
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studied of is (RTA) A reaction-diffusion model receptor-toxin-antibody interaction numerically.
A reaction-diffusion model of receptor-toxin-antibody (RTA) interaction is studied numerically.
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for the prediction data. of graph problem We evolving study
We study the problem of prediction for evolving graph data.
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efficient and to obtain formulation oracle solvers. convex allows inequalities The
The convex formulation allows to obtain oracle inequalities and efficient solvers.
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transport. Linked transport Without limited around applications data exclusively Data, to is
Without Linked Data, transport data is limited to applications exclusively around transport.
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these possible will because datasets. to data transport be be This linked will
This will be possible because transport data will be linked to these datasets.
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provide of bounds. method lower to exact guarantees approximations outer Our the
Our method guarantees to provide outer approximations of the exact lower bounds.
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kind a not is limited of network specific Our method structure. to
Our method is not limited to a specific kind of network structure.
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approaches. is computational to superior other existing The of that complexity
The computational complexity is superior to that of other existing approaches.
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viewed variables uncertainty as The values. their quantify to random parameters are about
The parameters are viewed as random variables to quantify uncertainty about their values.
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to i.e., of responses queries; Belief to conditional are interest. used nets probabilities compute
Belief nets are used to compute responses to queries; i.e., conditional probabilities of interest.
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variable. A a is the function a random parameters, hence of query
A query is a function of the parameters, hence a random variable.
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and variance. We accurate both approximations more mean query for develop
We develop more accurate approximations for both query mean and variance.
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