The projector is being frequently used in broad range of the photogrammetric measurements with the development of non-contact measurement in the close-range photogrammetry, because a projector can project any pattern onto the measured object for controlling and calculating. Before using a projector, the interior parameters of it have to be calibrated first. Hence, the projector calibration is a...

The behaviour of algorithms for very robust regression depends on the distance between the regression data and the outliers. We introduce a parameter λ that defines a parametric path in the space of models and enables us to study, in a systematic way, the properties of estimators as the groups of data move from being far apart to close together. We examine, as a function of λ, the variance and ...

Classi cation is an important problem in data mining. Given an example x and a class c, a classi er usually works by estimating the probability of x being member of c (i.e., membership probability). Well calibrated classi ers are those able to provide accurate estimates of class membership probabilities, that is, the estimated probability p̂(c|x) is close to p(c|p̂(c|x)), which is the true, em...

abstract area-reduction method is one of the most common experimental methods that determines the sediment distribution in reservoirs. in this method, reservoirs are geometrically divided into four types. for all reservoir types, parameters are achieved based on a limited number of reservoirs which leads to large scale errors for prediction of this method. so suitable parameters can be achieved...

Long-term carbon (C) cycle feedbacks to climate depend on the future dynamics of soil organic carbon (SOC). Current models show low predictive accuracy at simulating contemporary SOC pools, which can be improved through parameter estimation. However, major uncertainty remains in global soil responses to climate change, particularly uncertainty in how the activity of soil microbial communities w...

This paper studies a dynamic agency problem which includes limited liability, moral hazard and adverse selection. The paper develops a robust approach to dynamic contracting based on calibrating the payoffs that would have been delivered by simple benchmark contracts that are attractive but infeasible, due to limited liability constraints. The resulting dynamic contracts are detail-free and sat...

The vebrane worldvolume theory in eleven dimensions is known to contain BPS threebrane solitons which can also be interpreted as a vebrane whose worldvolume is wrapped around a Riemann surface. By considering con gurations of intersecting vebranes and hence intersecting threebrane solitons, we determine the Bogomol'nyi equations for more general BPS con gurations. We obtain di erential equation...

We study fairness within the stochastic,multi-armed bandit (MAB) decision making framework. We adapt the fairness framework of “treating similar individuals similarly” [5] to this seŠing. Here, an ‘individual’ corresponds to an arm and two arms are ‘similar’ if they have a similar quality distribution. First, we adopt a smoothness constraint that if two arms have a similar quality distribution ...

The concept of simulating chosen information channels of a linear incoherent imaging system by projecting reference signals is proposed and the system's ability to restore severely distorted but stationary images is experimentally demonstrated. A particular instrument's object field is divided into N discrete 'points' whose individual simulated outputs is measured at N particular sampling point...

Excellent ranking power along with well calibrated probability estimates are needed in many classification tasks. In this paper, we introduce a technique, Calibrated Boosting-Forest1 that captures both. This novel technique is an ensemble of gradient boosting machines that can support both continuous and binary labels. While offering superior ranking power over any individual regression or clas...