A Combinatorial Approach to Some Sparse Matrix Problems
This dissertation considers two combinatorial problems arising in large-scale, sparse optimizaton. The first is the problem of approximating the Hessian matrix of a smooth, non-linear function by finite differencing, where the object is to minimize the required number of gradient evaluations. The second is to find as sparse a representation as possible of a given set of linear constraints.
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