نتایج جستجو برای: restarting vector

تعداد نتایج: 198310  

2014
Sun Jung Kim Joo Hun Lee Sulgi Kim Shunichi Nakagawa Heather Bertelson Julia Lam Ji Won Yoo

OBJECTIVE To examine how drug therapy patterns for osteoporosis have changed after the Medicare Physician Fee Schedule (MPFS) reimbursement reduction in 2007, in relation to follow-up bone mineral density (BMD) testing status. METHODS We used a retrospective temporal shift design to examine changes in drug therapy patterns before (Phase 1: January 1, 2005-December 31, 2006) and after (Phase 2...

Journal: :SIAM J. Scientific Computing 2001
Karl Meerbergen

This paper studies the solution of quadratic eigenvalue problems by the quadratic residual iteration method. The focus is on applications arising from nite-element simulations in acoustics. One approach is the shift-invert Arnoldi method applied to the linearized problem. When more than one eigenvalue is wanted, it is advisable to use locking or de-ation of converged eigenvectors (or Schur vect...

Journal: :Eng. Appl. of AI 2012
Gregor Papa Vida Vukasinovic Peter Korosec

Planning problems can be solved with a large variety of different approaches, and a significant amount of work has been devoted to the automation of planning processes using different kinds of methods. This paper focuses on the use of specific local search algorithms for real-world production planning based on experiments with real-world data, and presents an adapted local search guided by evol...

1992
Charles W. Anderson

Platt's resource-allocation network (RAN) (Platt, 1991a, 1991b) is modified for a reinforcement-learning paradigm and to "restart" existing hidden units rather than adding new units. After restarting, units continue to learn via back-propagation. The resulting restart algorithm is tested in a Q-Iearning network that learns to solve an inverted pendulum problem. Solutions are found faster on ave...

Journal: :SIAM Journal on Matrix Analysis and Applications 2014

Journal: :Journal of Optimization Theory and Applications 2022

Conditional gradient algorithms (aka Frank–Wolfe algorithms) form a classical set of methods for constrained smooth convex minimization due to their simplicity, the absence projection steps, and competitive numerical performance. While vanilla algorithm only ensures worst-case rate $${\mathcal {O}}(1/\epsilon )$$ , various recent results have shown that strongly functions on polytopes, method c...

2016
Masataka Yoshida Takahiro Takazono Masato Tashiro Tomomi Saijo Yoshitomo Morinaga Kazuko Yamamoto Shigeki Nakamura Yoshifumi Imamura Taiga Miyazaki Toyomitsu Sawai Tomoya Nishino Koichi Izumikawa Katsunori Yanagihara Hiroshi Mukae Shigeru Kohno

Streptococcal toxic shock syndrome caused by group B streptococcus (GBS) is a rare, but lethal disease. We experienced a 45-year-old woman with pustular psoriasis who developed toxic shock-like syndrome during infliximab treatment. Surprisingly, similar episodes recurred three times in one year with restarting of infliximab treatments. In the third episode, GBS were detected in blood, urine, an...

2016
Walid Krichene Alexandre M. Bayen Peter L. Bartlett

We study accelerated descent dynamics for constrained convex optimization. This dynamics can be described naturally as a coupling of a dual variable accumulating gradients at a given rate η(t), and a primal variable obtained as the weighted average of the mirrored dual trajectory, with weights w(t). Using a Lyapunov argument, we give sufficient conditions on η and w to achieve a desired converg...

2010
Martin Plátek Frantisek Mráz Markéta Lopatková

We provide a formal model of a stratificational dependency approach to natural language description. This formal model is motivated by an elementary method of analysis by reduction, which serves for describing correct sentence analysis. The model is based on enhanced restarting automata that assign a set of parallel dependency structures to every reduction of an input sentence. These structures...

2006
Frantisek Mráz Friedrich Otto Martin Plátek

Analysis by reduction is a method used in linguistics for checking the correctness of sentences of natural languages. This method is modelled by restarting automata. Here we introduce and study a new type of restarting automaton, the socalled t-sRL-automaton, which is an RL-automaton that is rather restricted in that it has a window of size 1 only, and that it works under a minimal acceptance c...

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