Search results for "parameter"
showing 10 items of 14056 documents
Transfer Learning with Convolutional Networks for Atmospheric Parameter Retrieval
2018
The Infrared Atmospheric Sounding Interferometer (IASI) on board the MetOp satellite series provides important measurements for Numerical Weather Prediction (NWP). Retrieving accurate atmospheric parameters from the raw data provided by IASI is a large challenge, but necessary in order to use the data in NWP models. Statistical models performance is compromised because of the extremely high spectral dimensionality and the high number of variables to be predicted simultaneously across the atmospheric column. All this poses a challenge for selecting and studying optimal models and processing schemes. Earlier work has shown non-linear models such as kernel methods and neural networks perform w…
Modeling temporal treatment effects with zero inflated semi-parametric regression models: The case of local development policies in France
2017
International audience; A semi-parametric approach is proposed to estimate the variation along time of the effects of two distinct public policies that were devoted to boost rural development in France over a similar period of time. At a micro data level, it is often observed that the dependent variable, such as local employment, does not vary along time, so that we face a kind of zero inflated phenomenon that cannot be dealt with a continuous response model. We introduce a conditional mixture model which combines a mass at zero and a continuous response. The suggested zero inflated semi-parametric statistical approach relies on the flexibility and modularity of additive models with the abi…
Joint Gaussian Processes for Biophysical Parameter Retrieval
2017
Solving inverse problems is central to geosciences and remote sensing. Radiative transfer models (RTMs) represent mathematically the physical laws which govern the phenomena in remote sensing applications (forward models). The numerical inversion of the RTM equations is a challenging and computationally demanding problem, and for this reason, often the application of a nonlinear statistical regression is preferred. In general, regression models predict the biophysical parameter of interest from the corresponding received radiance. However, this approach does not employ the physical information encoded in the RTMs. An alternative strategy, which attempts to include the physical knowledge, co…
Randomized Rx For Target Detection
2018
This work tackles the target detection problem through the well-known global RX method. The RX method models the clutter as a multivariate Gaussian distribution, and has been extended to nonlinear distributions using kernel methods. While the kernel RX can cope with complex clutters, it requires a considerable amount of computational resources as the number of clutter pixels gets larger. Here we propose random Fourier features to approximate the Gaussian kernel in kernel RX and consequently our development keep the accuracy of the nonlinearity while reducing the computational cost which is now controlled by an hyperparameter. Results over both synthetic and real-world image target detection…
An LP-based hyperparameter optimization model for language modeling
2018
In order to find hyperparameters for a machine learning model, algorithms such as grid search or random search are used over the space of possible values of the models hyperparameters. These search algorithms opt the solution that minimizes a specific cost function. In language models, perplexity is one of the most popular cost functions. In this study, we propose a fractional nonlinear programming model that finds the optimal perplexity value. The special structure of the model allows us to approximate it by a linear programming model that can be solved using the well-known simplex algorithm. To the best of our knowledge, this is the first attempt to use optimization techniques to find per…
Multispectral image denoising with optimized vector non-local mean filter
2016
Nowadays, many applications rely on images of high quality to ensure good performance in conducting their tasks. However, noise goes against this objective as it is an unavoidable issue in most applications. Therefore, it is essential to develop techniques to attenuate the impact of noise, while maintaining the integrity of relevant information in images. We propose in this work to extend the application of the Non-Local Means filter (NLM) to the vector case and apply it for denoising multispectral images. The objective is to benefit from the additional information brought by multispectral imaging systems. The NLM filter exploits the redundancy of information in an image to remove noise. A …
Implicit differentiation for fast hyperparameter selection in non-smooth convex learning
2022
International audience; Finding the optimal hyperparameters of a model can be cast as a bilevel optimization problem, typically solved using zero-order techniques. In this work we study first-order methods when the inner optimization problem is convex but non-smooth. We show that the forward-mode differentiation of proximal gradient descent and proximal coordinate descent yield sequences of Jacobians converging toward the exact Jacobian. Using implicit differentiation, we show it is possible to leverage the non-smoothness of the inner problem to speed up the computation. Finally, we provide a bound on the error made on the hypergradient when the inner optimization problem is solved approxim…
Thermal imaging ruled out as a supplementary assessment in patients with fibromyalgia: A cross-sectional study
2021
Background The diagnosis of fibromyalgia syndrome (FMS) syndrome is often complicated and relies on diagnostic criteria based mostly on the symptoms reported by patients. Implementing objective complementary tests would be desirable to better characterize this population. Objective The purpose of this cross-sectional study was to compare the skin temperature at rest using thermography in women with FMS and healthy women. Methods Eighty-six women with FMS and 92 healthy controls volunteered to participate. The temperature of all participants was measured by infra-red thermography, registering the skin surface temperature (minimum, maximum and average) at rest in different areas: neck, upper…
Effect of aggregation of a dispersed rigid filler on the elastic characteristics of a polymer composite
1986
We proposed a method for describing the effective elastic characteristics of a polymer composite with a rigid aggregating filler. An important feature of such a medium is the variable coupling of the inclusion phase in relation to its volume content. A change in the degree of coupling of the filler is accounted for by introducing an additional parameter. We examined a method of determining the coupling parameter from the results of statistical modeling of the geometry of the medium. Using the example of a calcite-HDPE composite, we showed that aggregation has a significant effect on the dependence of the elastic modulus on the volume content of filler; satisfactory agreement was obtained be…
Modelling Nannochloropsis gaditana Growth in Reactors with Different Geometries, Determination of Kinetic Parameters and Biochemical Analysis in Resp…
2022
Microalgae are unicellular and photosynthetic microorganisms which grow thanks to inorganic salts, CO2 and light, and find applications in several fields thanks to their variety. The industrial application of microalgae has not often been fully exploited because of a lack of information about how microalgae respond to inputs and to different growth environments. In the present work a model able to predict the microalgae growth in reactors with different geometries was developed. We combined a Monod-like model for the specific growth rate with the Lambert-Beer law of homogeneous light distribution in thick photobioreactors. Kinetic parameters related to the cultivation of the microalga Nanno…