The Trust-Region Approach
A Two-Stage Subspace Trust Region Approach for Deep Neural Network Training
... a trust region through a two-stage procedure: first inside the embedded positive curvature subspace, followed by a gradient descent ...This approach leads to a fast objective function decay, prevents ...
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A nonmonotone trust-region-approach with nonmonotone adaptive radius for solving nonlinear systems
... in which m(0) := 0 and 0 ≤ m(k) ≤ min { m(k − 1) + 1, N } with N ≥ 0. The theoretical and numerical results have shown that the proposed technique has some remarkable effects and improves both the possibility of finding ...
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Quasi-Newton Model-Trust Region Approach to Surrogate-Based Optimisation of Planar Metamaterial Structures
... synthesis approach for planar metamaterial ...ASM approach yields satisfactory results after only a few fine model ...this approach is a quasi-Newton model-trust region optimisation ...
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A Certified Trust Region Reduced Basis Approach to PDE-Constrained Optimization
... k e ∇µJ (µ) k . The corresponding definitions for the parabolic case are similar and thus omitted. We observe that the effectivities of the primal bounds are close to 1 for all cases considered, thus indicating very ...
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Fast Trust Region for Segmentation
... Abstract Trust region is a well-known general iterative approach to optimization which offers many advantages over stan- dard gradient descent ...this approach computes a global optimum of a ...
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The convergence of subspace trust region methods
... of trust region methods could possibly be ...adequate trust region at each iteration [ 42–47 ...of trust region method, which is the subspace trust region ...our ...
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Trust Region Policy Optimization for POMDPs
... We relaxed this hard threshold and analyzed PPO Section C Subsection C.2. We deploy the analysis in Eq. 11 and Eq. 13, apply the suggested changes to the plain PPO and exam- ine its performance in the variety of ...
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A trust-region based sequential linear programming approach for AC optimal power flow problems
... new trust-region based sequential linear programming algorithm to solve the AC optimal power flow (OPF) ...a trust-region to control the validity of the linear ...
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A trust region algorithm for heterogeneous multiobjective optimization
... common approach is scalarization, that is combining the objectives to ob- tain a scalar-valued function and optimize this surrogate problem with known methods for scalar optimization ...sum approach is a ...
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Efficient Trust Region Methods for Nonconvex Optimization
... In Chapter 3, we have proposed a general framework for solving smooth nonconvex optimization problems and proceeded to prove worst-case iteration complexity bounds for it. Our framework is flexible enough to cover a wide ...
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Convergence of Trust-Region Methods Based on Probabilistic Models
... 6.2 Random sample sets In the cases when function evaluations are not very expensive or can be obtained in parallel, there is less incentive to reuse old sample points for model building, because ensuring the model ...
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A trust region method for parabolic boundary control problems
... Our approach to minimization of the reduced quadratic model also differs from that in ...1 trust region bounds. We use the standard L 2 trust region and therefore do not include the ...
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CiteSeerX — A 2-BFGS updating in a trust region framework
... the trust region radius Δ k is decreased and either the subproblem (2) is resolved or a backtracking line search ([12, 21] ) is performed in order to obtain a new trial ...this approach is that ...
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Trust region versus line search for computing the optical flow
... Key words. Optical flow, optimization, trust region, line search, truncated Newton, multires- olution 1. Introduction. Optical flow is a problem that consists in finding the two- dimensional field that ...
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Trust Region Newton Method for Large-Scale Logistic Regression
... effective approach for large-scale uncon- strained optimization, but their use for logistic regression has not been fully ...This approach, called trust region Newton method, uses only ...
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Trust Region Newton Method for Large-Scale Logistic Regression
... effective approach for large-scale unconstrained op- timization, but their use for logistic regression has not been fully ...This approach, called trust region Newton method, uses only ...
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A second-derivative trust-region SQP method with a "trust-region-free" predictor step
... on trust-region methodology even though the predictor step is computed without a trust region radius; their algorithm is based on line-search ...
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NELSON REGION HOSPICE TRUST
... The Hospice nurse will display a high level of professional expertise appropriate to the service area and the community; and other health care providers will have access to specialist p[r] ...
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Trust Region Evolution Strategies
... Evolution Strategies (ES), a class of black-box optimization algorithms, has recently been demonstrated to be a viable al- ternative to popular MDP-based RL techniques such as Q- learning and Policy Gradients. ES ...
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A tensor trust region model for nonlinear system
... tensor trust-region subproblem model of the nonlinear equations is presented; (ii) the three dimensional symmetric tensor is replaced by interpolating function and gradient values from the most recent past ...
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