Results 11 to 20 of about 427,529 (281)
Stochastic Development Regression on Non-Linear Manifolds [PDF]
We introduce a regression model for data on non-linear manifolds. The model describes the relation between a set of manifold valued observations, such as shapes of anatomical objects, and Euclidean explanatory variables.
EP Hsu +15 more
core +3 more sources
Stochastic Low-Rank Kernel Learning for Regression [PDF]
We present a novel approach to learn a kernel-based regression function. It is based on the useof conical combinations of data-based parameterized kernels and on a new stochastic convex optimization procedure of which we establish convergence guarantees.
Anthoine, Sandrine +4 more
core +5 more sources
Nonlinear stochastic modelling with Langevin regression [PDF]
Many physical systems characterized by nonlinear multiscale interactions can be modelled by treating unresolved degrees of freedom as random fluctuations. However, even when the microscopic governing equations and qualitative macroscopic behaviour are known, it is often difficult to derive a stochastic model that is consistent with observations.
Callaham, J. +3 more
openaire +7 more sources
Regression and progression in stochastic domains [PDF]
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Belle, Vaishak; id_orcid 0000-0001-5573-8465 +1 more
openaire +2 more sources
Stochastically ordered multiple regression [PDF]
In various application areas, prior information is available about the direction of the effects of multiple predictors on the conditional response distribution. For example, in epidemiology studies of potentially adverse exposures and continuous health responses, one can typically assume a priori that increasing the level of an exposure does not lead ...
Bornkamp, Björn +2 more
openaire +3 more sources
Trend detection and stochastic simulation prediction of streamflow at Yingluoxia hydrological station, Heihe River Basin, China [PDF]
Investigating long-term variation and prediction of streamflow are critical to regional water resource management and planning. Under the continuous influence of climate change and human activity, the trends of hydrologic time series are nonstationary ...
Chenglong ZHANG,Mo LI,Ping GUO
doaj +1 more source
FPGA-Based Implementation of Stochastic Configuration Networks for Regression Prediction
The implementation of neural network regression prediction based on digital circuits is one of the challenging problems in the field of machine learning and cognitive recognition, and it is also an effective way to relieve the pressure of the Internet in
Yunqi Gao +4 more
doaj +1 more source
Stochastic Tree Ensembles for Regularized Nonlinear Regression [PDF]
This paper develops a novel stochastic tree ensemble method for nonlinear regression, which we refer to as XBART, short for Accelerated Bayesian Additive Regression Trees. By combining regularization and stochastic search strategies from Bayesian modeling with computationally efficient techniques from recursive partitioning approaches, the new method ...
Jingyu He, P. Richard Hahn
openaire +2 more sources
Stochastic Restricted LASSO-Type Estimator in the Linear Regression Model
Among several variable selection methods, LASSO is the most desirable estimation procedure for handling regularization and variable selection simultaneously in the high-dimensional linear regression models when multicollinearity exists among the ...
Manickavasagar Kayanan +1 more
doaj +1 more source
The COVID-19 pandemic has had worldwide devastating effects on human lives, highlighting the need for tools to predict its development. The dynamics of such public-health threats can often be efficiently analyzed through simple models that help to make ...
P.L. de Andres +2 more
doaj +1 more source

