Abstract
We show that with recently developed derandomization techniques, one can convert Clarkson's randomized algorithm for linear programming in fixed dimension into a linear-time deterministic algorithm. The constant of proportionality is d O(d) , which is better than those for previously known algorithms. We show that the algorithm works in a fairly general abstract setting, which allows us to solve various other problems, e.g., computing the minimum-volume ellipsoid enclosing a set of n points and finding the maximum volume ellipsoid in the intersection of n halfspaces.
Original language | English (US) |
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Pages (from-to) | 579-597 |
Number of pages | 19 |
Journal | Journal of Algorithms |
Volume | 21 |
Issue number | 3 |
DOIs | |
State | Published - Jan 1 1996 |
All Science Journal Classification (ASJC) codes
- Control and Optimization
- Computational Mathematics
- Computational Theory and Mathematics