Searching for "Complexity of linear problems." – sorted by Relevance.
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Computationally Efficient Stochastic Realization for Internal Multiscale Autoregressive Models
- in problem size. We also introduce an approximation to obtain an algorithm that has complexity linear
- Cited by 5 (4 self) – Add To MetaCart
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Computational Complexity of Continuous Problems
- with huge d. We are interested in the complexity of linear multivariate problems in various settings. 3
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Overview of Information-Based Complexity
- IBC results on complexity of linear problems. They are expressed in terms of singular values of S d
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Towards an optimization of the routing parameters for IP networks
- . The previous possibilities to reduce the complexity of the linear problem both presolved the values of certain
- Cited by 9 (3 self) – Add To MetaCart
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Improved Solution Enclosures for Over- and Underdetermined Interval Linear Systems
- basis for the solution of an over- /underdetermined interval (real or complex) linear problem (2), (3
- Cited by 3 (1 self) – Add To MetaCart
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Efficient Multiscale Stochastic Realization
- [8], and fast linear least squares estimation [3]. The estimator has computational complexity linear
- Cited by 6 (3 self) – Add To MetaCart
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A Subspace Approximation Method for the Quadratic Eigenvalue Problem
- .16) has complex matrices M proj , C proj , and K proj , resulting in a complex linearized problem
- Cited by 2 (0 self) – Add To MetaCart
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Solving markov random fields with spectral relaxation
- the total algorithm complexity is linear in the problem description length. Note this compares very
- Cited by 2 (0 self) – Add To MetaCart
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Tractability of quasilinear problems I: general results, II: second-order elliptic problems
- typical when studying the complexity of linear problems; see [12, Sect. 4.5.1]. On the other hand
- Cited by 2 (1 self) – Add To MetaCart

