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Strong law of large number of a class of super-diffusions
Spatial autoregression Dynamic panels Fixed e¤ects Quasi-maximum likelihood estima
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2016/1/19
Strong law of large number of a class of super-diffusions.
Complexity of Non-Adaptive Optimization Algorithms for a Class of Diffusions
Global optimization average-case complexity diffusion processes
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2015/7/8
This paper is concerned with the analysis of the average error in approximating the global minimum of a 1-dimensional, time-homogeneous diffusion by non-adaptive methods. We derive the limiting distri...
On a class of spatial discretizations of equations of the nonlinear Schrödinger type
Discrete nonlinear schrodinger equation nonlinear discrete model and discrete
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2014/12/25
We demonstrate the systematic derivation of a class of discretizations of nonlinear Schrödinger (NLS) equations for general polynomial nonlinearity whose stationary solutions can be found from a ...
A delimitation of the support of optimal designs for Kiefer's $φ_p$-class of criteria
Approximate design optimum design support points design algorithm MSC62K05 90C46
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2013/4/28
The paper extends the result of Harman and Pronzato [Stat. & Prob. Lett., 77:90--94, 2007], which corresponds to $p=0$, to all strictly concave criteria in Kiefer's $\phi_p$-class. Let $\xi$ be any de...
On a class of space-time intrinsic random functions
Fox’sH-function generalized covariance function Mat′ern covariance function
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2013/4/28
Power law generalized covariance functions provide a simple model for describing the local behavior of an isotropic random field. This work seeks to extend this class of covariance functions to spatia...
Concepts and a case study for a flexible class of graphical Markov models
Concepts a case study a flexible class graphical Markov models
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2013/4/27
With graphical Markov models, one can investigate complex dependences, summarize some results of statistical analyses with graphs and use these graphs to understand implications of well-fitting models...
One-Class Support Measure Machines for Group Anomaly Detection
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2013/4/27
We propose one-class support measure machines (OCSMMs) for group anomaly detection which aims at recognizing anomalous aggregate behaviors of data points. The OCSMMs generalize well-known one-class su...
Statistically adaptive learning for a general class of cost functions (SA L-BFGS)
Statistically adaptive learning general class cost functions
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2012/11/23
We present a system that enables rapid model experimentation for tera-scale machine learning with trillions of non-zero features, billions of training examples, and millions of parameters. Our contrib...
On computation of clustering coefficient in a class of random networks
random graph clustering degree of separation
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2012/9/18
The random networks enriched with additional structures asmetric and group-symmetry in background metric space are investigated. The important quantities like he clustering coefficient as well as the ...
On adaptive wavelet estimation of a class of weighted densities
Weighted density density estimation plug-in approach wavelets block thresholding reliability series system parallel system.
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2012/9/18
We investigate the estimation of a weighted density taking the formg=w(F)f, where fdenotes an unknown density,Fthe associated distribution function andwis a known (non-negative) weight.Such a class en...
Multi-Instance Learning with Any Hypothesis Class
Multiple-instance learning learning theory sample complexity PAC learning
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2011/7/19
In the supervised learning setting termed Multiple-Instance Learning (MIL), the examples are bags of instances, and the bag label is a function of the labels of its instances. Typically, this function...
Abstract art grandmasters score like class D amateurs
Abstract art grandmasters score like class D amateurs
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2011/7/6
Hawley-Dolan and Winner had asked the art students to compare paintings by abstract artists with paintings made by a child or by an animal. In 67% of the cases, art students said that the painting by ...
Exact recording of Metropolis-Hastings-class Monte Carlo simulations using one bit per sample
Markov chain Monte Carlo Metropolis-Hastings information theory data representation
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2011/6/21
The Metropolis-Hastings (MH) algorithm is the prototype for a class of Markov chain Monte Carlo methods
that propose transitions between states and then accept or reject the proposal. These methods g...
A New Class of Backward Stochastic Partial Differential Equations with Jumps and Applications
Backward Stochastic Partial Differential Equations with Jumps High-Order Partial Differential Operator Vector Partial Differential Equation Existence and Uniqueness Random Environment
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2011/6/21
We formulate a new class of stochastic partial differential equations (SPDEs), named
high-order vector backward SPDEs (B-SPDEs) with jumps, which allow the high-order
integral-partial differential o...
Identification and well-posedness in a class of nonparametric problems
Identification well-posedness nonparametric problems
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2010/10/19
This is a companion note to Zinde-Walsh (2010), arXiv:1009.4217v1[MATH.ST], to clarify and extend results on identification in a number of problems that lead to a system of convolution equations. Exam...