Results 31 to 40 of about 4,779,838 (300)
Adaptive-batch stochastic gradient descent for constrained optimization based on relaxed barrier functions [PDF]
Iranian Journal of Numerical Analysis and OptimizationStochastic Gradient Descent (SGD) is the cornerstone of large-scale optimization; however, its application to problems with a vast number of constraints remains a significant challenge.
Abdelouakil Fillali +2 more
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FireBackground: Wildfire modelers rely on Monte Carlo simulations of wildland fire to produce burn probability maps. These simulations are computationally expensive.
Valentin Waeselynck, David Saah
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Stochastic Recursive Gradient Support Pursuit and Its Sparse Representation Applications
Sensors, 2020 In recent years, a series of matching pursuit and hard thresholding algorithms have been proposed to solve the sparse representation problem with ℓ0-norm constraint.
Fanhua Shang +5 more
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Stress-weighted spatial averaging of random fields in geotechnical risk assessment
Studia Geotechnica et Mechanica, 2021 Effects of spatial fluctuations of soil parameters are considered in a new context – considering variability of soil parameters in conjunction with non-uniform stress fields, which can locally amplify (or suppress) subsoil inhomogeneities.
Brząkała Włodzimierz
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Variance reduction for discretised diffusions via regression
, 2018 In this paper we present a novel approach towards variance reduction for discretised diffusion processes. The proposed approach involves specially constructed control variates and allows for a significant reduction in the variance for the terminal ...
Tigran Nagapetyan +7 more
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AN ADAPTIVE COMPOSITE QUANTILE APPROACH TO DIMENSION REDUCTION [PDF]
, 2014 Sufficient dimension reduction [Li 1991] has long been a prominent issue in multivariate nonparametric regression analysis. To uncover the central dimension reduction space, we propose in this paper an adaptive composite quantile approach.
Kong, Efang
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IEEE Access, 2020 The power consumption at the receiver side will be dramatically increased in the millimetre-wave and massive multiple-input-multiple-output (MIMO) communication systems due to the wide bandwidth and a large number of antennas adopted.
Yi Gong +3 more
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Model-independent hedging strategies for variance swaps [PDF]
, 2011 A variance swap is a derivative with a path-dependent payoff which allows investors to take positions on the future variability of an asset. In the idealised setting of a continuously monitored variance swap written on an asset with continuous paths, it ...
Klimmek, Martin +3 more
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A decomposition approach to variance reduction [PDF]
Proceedings of the 17th conference on Winter simulation - WSC '85, 1985 For analyzing stochastic models, simulation trades the tractability problems of analytical techniques for the problem of sampling variability. Variance reduction techniques (VRTs) attack this problem by transforming the simulation experiment in a way that makes it more statistically efficient.
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Variance Reduction in Simulations of Loss Models [PDF]
Operations Research, 1999 We propose a new estimator of steady-state blocking probabilities for simulations of stochastic loss models that can be much more efficient than the natural estimator (ratio of losses to arrivals). The proposed estimator is a convex combination of the natural estimator and an indirect estimator based on the average number of customers in service ...
Rayadurgam Srikant, Ward Whitt
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