Variable splitting based algorithms
On variable splitting for Markov chain Monte Carlo
... is based on a technique called variable ...optimization algorithms can provide confidence intervals on the pointwise ...simulation- based methods such as Markov chain Monte Carlo (MCMC) [8] to ...
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Efficient Sampling through Variable Splitting-inspired Bayesian Hierarchical Models
... techniques based on variational optimization have received a lot of interest over the past decade leading to fast, efficient and distributed ...Robbins-Monro algorithms [2] and distributed optimization ...
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On variable splitting for Markov chain Monte Carlo
... d based on (noisy) observations y ∈ R n ...is based on a technique called variable ...optimization algorithms can provide confidence intervals on the pointwise ...simulation- based ...
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Model-assisted variable clustering: minimax-optimal recovery and algorithms
... is based on data splitting: the estimators are built from a training sample, and then the selection involves an independent test sample (Hold-Out ...
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Limits of Trilateration-Based Sensor Placement Algorithms
... IV. S IMULATION RESULTS As the purpose of the beacons is to localize a mobile robot, the performances of the configurations given by the GA are tested on the localization accuracy of a differential-drive mobile robot ...
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Structure-based algorithms for protein-protein interactions
... three algorithms in the case of fitting the GroEL subunit into the ...other algorithms, which exhaustively search all the space of possible ...tested algorithms have their own advantages and ...
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Algorithms for Computing Cubatures Based on Moment Theory
... In this univariate case, minimal inside quadratures with positive weights are known and called Gaussian quadratures (see e.g.. A Gaussian quadrature with r nodes is of degree 2r − 1.[r] ...
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Approximation algorithms for grammar-based data compression
... The smallest grammar problem is also relevant to identifying important patterns in a string, since such patterns naturally correspond to nonterminals in a compact gr[r] ...
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Approximation Algorithms for Model-Based Compressive Sensing
... approximation algorithms, i.e., algorithms which find a signal in the model that only approximately minimizes the tail ...approximation algorithms has emerged over the last 15 years, encompassing a ...
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Evaluating product-based possibilistic networks learning algorithms
... 0.4 1 0.1 Fig. 1. Example of a product-based possibilistic network 3.2 Possibilistic networks structure learning By analogy to Bayesian networks, structure learning methods could be catego- rized into three ...
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RFID network topology design based on Genetic Algorithms
... Keywords-Genetic Algorithms; Radio Frequency Identification; Network Planning; Network Topology ...be based on different objectives such as coverage area, interference reduction, number of tags detected and ...
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Self-calibrating nonlinear reconstruction algorithms for variable density sampling and parallel reception MRI
... Index Terms— Prospective compressed sensing, parallel recep- tion, non-Cartesian trajectories, nonlinear reconstruction. 1. INTRODUCTION Magnetic Resonnance Imaging (MRI) is a key imaging technique to probe soft tissues ...
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Affordance-based control of a variable-autonomy telerobot
... recognize a model based on a pre-defined success probability [16]. Papazov et al. use an offline, model-preprocessing phase in addition to an online object recognition algorithm, demonstrating recognition of ...
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Simulations of Kinetic Electrostatic Electron Nonlinear (KEEN) Waves with Variable Velocity Resolution Grids and High-Order Time-Splitting
... The variable grid technique allows the inner v-space region to shrink in absolute size while maintaining high resolution within, without requir- ing massive fine scale resolution in the exterior velocity ...a ...
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Distance priority based multicast routing in WDM networks considering sparse light splitting
... Light Splitting, Distance Priority, Light-Tree Computation, WDM network ...called splitting capability. Note that optical switches with splitting capability are always much more expensive to build ...
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Isthmus-based Parallel and Asymmetric 3D Thinning Algorithms
... onsider liques. A lique is a set of mutually adja
ent voxels. Then, we identify the riti
al kernel of the obje
t, a ording to some de nitions, whi
h is a union of liques. The main theorem of the riti
al kernels ...
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Homotopy based algorithms for L0-regularized least-squares
... qualitatively good for CSBR and ℓ 0 -PD, the SE and TP scores are very weak. It is hard to discriminate the performance of algorithms because these measures are very weak for all considered algorithms. ...
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Latency-Based Anycast Geolocation: Algorithms, Software, and Datasets
... by algorithms, such as, for instance, known landmass areas (replicas are unlikely to be out at sea) and locations of major metropolitan areas (replicas might be situated close to these, in order to promote low ...
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Delaunay Triangulation Based Surface Reconstruction: Ideas and Algorithms
... Unité de recherche INRIA Sophia Antipolis 2004, route des Lucioles - BP 93 - 06902 Sophia Antipolis Cedex France Unité de recherche INRIA Futurs : Parc Club Orsay Université - ZAC des Vi[r] ...
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Fast Approximation Algorithms for Task-Based Runtime Systems
... BEAUMONT . accelerators. In this context, developing optimized hand-tuned kernels for all these architectures turns out to be extremely costly. Third, CPUs and GPUs of the same node share many resources (caches, ...
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