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Convex Analysisの二,三の進展について
徹 丸山
- Vol. 70, Iss: 1, pp 97-119
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The article was published on 1977-02-01 and is currently open access. It has received 5933 citations till now.read more
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References
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Journal ArticleDOI
Relaxation methods for minimum cost ordinary and generalized network flow problems
Dimitri P. Bertsekas,Paul Tseng +1 more
TL;DR: These algorithms are based on iterative improvement of a dual cost and operate in a manner that is reminiscent of coordinate ascent and Gauss-Seidel relaxation methods, and are found to be several times faster on standard benchmark problems, and faster by an order of magnitude on large, randomly generated problems.
Journal ArticleDOI
An $O(1/k)$ Gradient Method for Network Resource Allocation Problems
TL;DR: This paper develops a completely distributed fast gradient method for solving the dual of the NUM problem, and shows that the generated primal sequences converge to the unique optimal solution of theNUM problem at rate O(1/k).
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Rate Region of the Quadratic Gaussian Two-Encoder Source-Coding Problem
TL;DR: The rate region of the quadratic Gaussian two-encoder source-coding problem is determined and the techniques can be used to determine the sum-rate of some generalizations of this classical problem.
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Modeling and optimization of risk
TL;DR: The most recent advances in the context of decision making under uncertainty are surveyed, with an emphasis on the modeling of risk-averse preferences using the apparatus of axiomatically defined risk functionals and their connection to utility theory, stochastic dominance, and other more established methods.
Proceedings ArticleDOI
Concise Integer Linear Programming Formulations for Dependency Parsing
TL;DR: This formulation of the problem of non-projective dependency parsing as a polynomial-sized integer linear program is able to handle non-local output features in an efficient manner and is compatible with prior knowledge encoded as hard constraints, and can also learn soft constraints from data.