Results 21 to 30 of about 2,159,110 (277)
Improving Random Projections With Extra Vectors to Approximate Inner Products
IEEE Access, 2020 This research concerns itself with increasing the accuracy of random projections used to quickly approximate the inner products of data vectors from a given dataset by adding additional information, namely, adding and storing more extra known vectors to ...
Yulong Li +3 more
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Integrated Variance Reduction Strategies [PDF]
Proceedings of 1993 Winter Simulation Conference - (WSC '93), 1993 In this paper we develop strategies for integrating certain well-known variance reduction techniques to estimate a mean response in a finite-horizon simulation experiment. Our building blocks are the techniques of conditional expectation, correlation induction, and control variates.
Athanassios N. Avramidis +1 more
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Stochastic Momentum Method With Double Acceleration for Regularized Empirical Risk Minimization
IEEE Access, 2019 Momentum acceleration technique is famously known for building gradient-based algorithms with fast convergence in large-scale optimization. Recently, Nesterov 's momentum and Katyusha momentum have significantly improved the convergence for stochastic ...
Zhijian Luo, Siyu Chen, Yuntao Qian
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A Generative Adversarial Network Approach to Calibration of Local Stochastic Volatility Models
Risks, 2020 We propose a fully data-driven approach to calibrate local stochastic volatility (LSV) models, circumventing in particular the ad hoc interpolation of the volatility surface.
Christa Cuchiero +2 more
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Variance Reduction For A Discrete Velocity Gas [PDF]
, 2011 We extend a variance reduction technique developed by Baker and Hadjiconstantinou [1] to a discrete velocity gas. In our previous work, the collision integral was evaluated by importance sampling of collision partners [2].
Goldstein, D. B. +2 more
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Mathematics, 2023 Monte Carlo simulation is performed with uniformly distributed U(0,1) pseudo-random numbers. Because the numbers are generated from a mathematical formula, they will contain some serial correlation, even if very small.
Dennis Ridley, Pierre Ngnepieba
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Implementation of variance reduction techniques applied to the pricing of investment certificates [PDF]
Risk Management Magazine, 2023 Certificates are structured financial instruments that aim to provide investors with investment solutions tailored to their needs. Certificates can be modeled using a bond component and a derivative component, typically an options strategy.
Anna Bottasso +3 more
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Variance Reduction of Sequential Monte Carlo Approach for GNSS Phase Bias Estimation
Mathematics, 2020 Global navigation satellite systems (GNSS) are an important tool for positioning, navigation, and timing (PNT) services. The fast and high-precision GNSS data processing relies on reliable integer ambiguity fixing, whose performance depends on phase bias
Yumiao Tian, Maorong Ge, Frank Neitzel
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Semi-Stochastic Gradient Descent Methods
Frontiers in Applied Mathematics and Statistics, 2017 In this paper we study the problem of minimizing the average of a large number of smooth convex loss functions. We propose a new method, S2GD (Semi-Stochastic Gradient Descent), which runs for one or several epochs in each of which a single full gradient
Jakub Konečný, Peter Richtárik
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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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