Results 41 to 50 of about 39,793 (262)
ROBUST QUASI-NEWTON EQUATIONS IN QUASI-NEWTON METHOD FOR SOLVING UNCONSTRAINED OPTIMIZATION PROBLEMS
BarekengQuasi-Newton methods are among the most widely used and effective general-purpose algorithms for unconstrained optimization. These methods traditionally rely on the quasi-Newton equation, which serves as the foundation for updating approximations of the
Basim A. Hassan, Manal I. Mohammed
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Journal of Applied Mathematics, 2014 The numerical solution of optimal control problems by direct collocation is a widely used approach. Quasi-Newton approximations of the Hessian of the Lagrangian of the resulting nonlinear program are also common practice.
Jonas Asprion +2 more
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On the construction of probabilistic Newton-type algorithms
, 2017 It has recently been shown that many of the existing quasi-Newton algorithms can be formulated as learning algorithms, capable of learning local models of the cost functions.
Schön, Thomas B., Wills, Adrian G.
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Numerical Modeling of Photothermal Self‐Excited Composite Oscillators
Advanced Robotics Research, EarlyView.We present a numerical framework for simulating photothermal self‐excited oscillations. The driving mechanism is elucidated by highlighting the roles of inertia and overshoot, as well as the phase lag between the thermal moment and the oscillation angle, which together construct the feedback loop between the system state and the environmental stimulus.
Zixiao Liu +6 more
wiley +1 more source
Quasi-Newton Methods for Markov Chain Monte Carlo [PDF]
, 2011 The performance of Markov chain Monte Carlo methods is often sensitive to the scaling and correlations between the random variables of interest. An important source of information about the local correlation and scale is given by the Hessian matrix of ...
Chain Monte Carlo +2 more
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Advanced Science, EarlyView.Prolonged exposure to stiff extracellular matrix drives cancer‐associated fibroblasts into a persistently activated myofibroblast state. Two parallel pathways are identified: β1 integrin activation smoothens the nuclear lamina to reduce lamin–chromatin contacts, while the formin mDia2 regulates nuclear actin to alter chromatin organization.
Swathi Packirisamy +4 more
wiley +1 more source
A quasi-Newton proximal splitting method [PDF]
, 2012 A new result in convex analysis on the calculation of proximity operators in certain scaled norms is derived. We describe efficient implementations of the proximity calculation for a useful class of functions; the implementations exploit the piece-wise ...
Becker, Stephen, Fadili, M. Jalal
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Advanced Science, EarlyView.An entity‐centric foundation model, GloPath, is introduced for comprehensive glomerular lesion assessment from routine renal biopsy images. Trained on over one million glomeruli, the framework enables robust lesion recognition, grading, and cross modality diag nosis, while uncovering large‐scale clinicopathological associations.
Qiming He +28 more
wiley +1 more source
Optimal Conditioning of Quasi-Newton Methods [PDF]
Mathematics of Computation, 1970 Quasi-Newton methods accelerate gradient methods for minimizing a function by approximating the inverse Hessian matrix of the function. Several papers in recent literature have dealt with the generation of classes of approximating matrices as a function of a scalar parameter.
Shanno, D. F., Kettler, P. C.
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An improved quasi-Newton equation on the quasi-Newton methods for unconstrained optimizations
Indonesian Journal of Electrical Engineering and Computer Science, 2021 <span><span>Quasi-Newton methods are a class of numerical methods for </span>solving the problem of unconstrained optimization. To improve the overall efficiency of resulting algorithms, we use the quasi-Newton methods which is interesting for quasi-Newton equation.
Basim Abbas Hassan +4 more
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