Results 231 to 240 of about 427,529 (281)

Ribosome demand links transcriptional bursts to protein expression noise. [PDF]

Elife
Pal S, Ray U, Dhar R.
europepmc   +1 more source

Geochemical fingerprinting and machine learning for authenticating sparkling wine origins. [PDF]

NPJ Sci Food
Lu Y, Doerr C, Sebilo M.
europepmc   +1 more source

Coral-YOLO: An Intelligent Optical Vision Sensing Framework for High-Fidelity Marine Habitat Monitoring and Forecasting. [PDF]

Sensors (Basel)
Tao J, Tian H, Huang S, Ye Y, Xiong Y, Huang S, Qin J, Yin Y, Zhang J, Tang Y, Wu J.   +10 more
europepmc   +1 more source

PLS regression on a stochastic process [PDF]

Computational Statistics and Data Analysis, 2005
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Preda, Cristian, Saporta, Gilbert
exaly   +4 more sources

Clusterwise PLS regression on a stochastic process [PDF]

Computational Statistics and Data Analysis, 2005
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Preda, Cristian, Saporta, Gilbert
exaly   +3 more sources

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Heuristics for the regression of stochastic simulations

Journal of Simulation, 2013
Modelling and simulation environments that are stochastic in nature present a multitude of problems in the creation of meta-models, notably the reduction of the quality of fit due to statistical er...
Andrew James Turner, Santiago Balestrini-Robinson, Dimitri N. Mavris   +2 more
openaire   +1 more source

Switching regression metamodels in stochastic simulation

European Journal of Operational Research, 2016
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
M. Isabel Reis dos Santos, Pedro M. Reis dos Santos   +1 more
openaire   +1 more source

On the Averaged Stochastic Approximation for Linear Regression

SIAM Journal on Control and Optimization, 1996
Summary: For a linear regression function the average of stochastic approximation with constant gain is considered. In case of ergodic observations almost sure convergence is proved, where the limit is biased with small bias for small gain. For independent and identically distributed observations and also under martingale and mixing assumptions ...
Györfi, László, Walk, Harro
openaire   +2 more sources