Results 51 to 60 of about 36,010,976 (311)
A new, globally convergent Riemannian conjugate gradient method [PDF]
, 2013 This article deals with the conjugate gradient method on a Riemannian manifold with interest in global convergence analysis. The existing conjugate gradient algorithms on a manifold endowed with a vector transport need the assumption that the vector ...
Iwai, Toshihiro, Sato, Hiroyuki
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The alternating descent conditional gradient method for sparse inverse problems [PDF]
IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2015 We propose a variant of the classical conditional gradient method (CGM) for sparse inverse problems with differentiable measurement models. Such models arise in many practical problems including superresolution, time-series modeling, and matrix ...
Nicholas Boyd +2 more
semanticscholar +1 more source
Optimal H2 Moment Matching-Based Model Reduction for Linear Systems through (Non)convex Optimization
Mathematics, 2022 In this paper, we compute a (local) optimal reduced order model that matches a prescribed set of moments of a stable linear time-invariant system of high dimension. We fix the interpolation points and parametrize the models achieving moment-matching in a
Ion Necoara, Tudor-Corneliu Ionescu
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Background field method in the gradient flow
, 2015 In perturbative consideration of the Yang--Mills gradient flow, it is useful to introduce a gauge non-covariant term ("gauge-fixing term") to the flow equation that gives rise to a Gaussian damping factor also for gauge degrees of freedom. In the present
Suzuki, Hiroshi
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Policy Gradient Methods for Robotics [PDF]
2006 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2006 The acquisition and improvement of motor skills and control policies for robotics from trial and error is of essential importance if robots should ever leave precisely pre-structured environments. However, to date only few existing reinforcement learning methods have been scaled into the domains of high-dimensional robots such as manipulator, legged or
Jan Peters 0001, Stefan Schaal
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DronesIn order to improve the network performance of multi-unmanned ground vehicle (UGV) systems in urban environments, this article proposes a novel online autonomous motion-control method for the relay UAV.
Cancan Tao, Bowen Liu
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Orthogonal Functions Applied in Antenna Positioning
Advances in Electrical and Computer Engineering, 2010 In this paper, we present a method for designing orthogonal, Legendre type filters. Realization of these filters is very simple and they are very fast, robust and precise.
JOVANOVIC, Z. +5 more
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Scholarpedia, 2010 A policy gradient method is a reinforcement learning approach that directly optimizes a parametrized control policy by gradient descent. It belongs to the class of policy search techniques that maximize the expected return of a policy in a fixed policy class while traditional value function approximation approaches derive policies from a value function.
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Mathematics, 2022 In this paper, a hybrid gradient simulated annealing algorithm is guided to solve the constrained optimization problem. In trying to solve constrained optimization problems using deterministic, stochastic optimization methods or hybridization between ...
Khalid Abdulaziz Alnowibet +4 more
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Pediatric Blood &Cancer, EarlyView.ABSTRACT Purpose Pediatric central nervous system (CNS) tumors often recur despite multimodality therapy. Although re‐irradiation (re‐RT) has historically been limited by concerns for severe late toxicities, modern techniques have renewed interest in this approach. Proton therapy provides dosimetric advantages that may enable curative re‐treatment with
Jin‐Ho Song +15 more
wiley +1 more source