Some Possible Papers for Final CS6676 Homework
Modified Cholesky Factorization
Schnabel and Eskow, SIAM Journal on Scientific and Statistical Computing,
Vol. 11, 1990, pp. 1136 - 1158
Trust Region Methods and Analysis
More' and Sorensen, SIAM Journal on Scientific and Statistical Computing,
Vol. 4, 1983, pp. 553-572 (hookstep method)
Shultz, Schnabel, and Byrd, SIAM Journal on Numerical Analysis
Vol. 22, 1985, pp. 47-67 (general trust region theory/methods)
Byrd, Schnabel, and Shultz, Mathematical Programming,
Vol. 40, 1988, pp. 247-263 (approximate hookstep method)
Secant Methods
Byrd, Nocedal, and Yuan, SIAM Journal on Numerical Analysis,
Vol. 24, 1987, pp. 1171-1189 (analysis of a class of secant updates)
Khalfan, Byrd, and Schnabel, SIAM Journal on Optimization,
Vol. 3, 1993, pp. 1-24 (symmetric rank one update)
Large Scale Optimization
Dembo, Eisenstat, and Steihaug, SIAM Journal on Numerical Analysis,
Vol. 19, 1982, pp. 400-408 (truncated Newton)
Steihaug, SIAM Journal on Numerical Analysis, Vol. 20, 1983, pp. 626-637
(truncated Newton with trust region)
Buckley and Lenir, Mathematical Programming, Vol. 27, 1985, pp. 155-175
(limited memory BFGS and relation to conjugate gradient)
Nash, SIAM Journal on Scientific and Statistical Computing,
Vol. 6, 1985, pp. 599-616 (truncated Newton with preconditioned CG)
Nocedal, Mathematics of Computation, Vol. 35, 1980, pp. 773-782
(limited memory BFGS)
Nash and Nocedal, SIAM Journal on Optimization, Vol. 1, pp. 358-372
(limited memory BFGS vs truncated Newton)
Griewank and Toint, Numerische Mathematik, Vol. 39, 1982, pp. 119-137
(partially separable secant methods)
Finite Difference Derivative Approximation
Coleman and More', SIAM Journal on Numerical Analysis,
Vol. 20, 1983, pp. 187-209 (sparse finite difference Jacobians)
Coleman and More', SIAM Journal on Numerical Analysis,
Vol. 21, 1984, pp. 243-270 (sparse finite difference Hessians)
Parallel Optimization
Byrd, Schnabel, and Shultz, Mathematical Programming,
Vol. 42, 1988, pp. 273-306 (parallel unconstrained optimization)
Orthogonal Distance Regression
Boggs, Byrd, and Schnabel, SIAM Journal on Scientific and Statistical Computing,
Vol. 8, 1987, pp. 1052-1078
More complex models for nonlinear equations / unconstrained optimization
Schnabel and Frank, SIAM Journal on Numerical Analysis
Vol. 22, 1985, pp. 47-67 ("tensor methods" for nonlinear equations)
Schnabel and Chow, SIAM Journal on Optimization,
Vol. 1, 1991, pp. 293-315 ("tensor methods" for unconstrained optimization)
Best authors ever for an optimization paper
Hart and Soul, "Quasi-Newton methods for discretized nonlinear boundary
value problems", IMA Journal of Applied Mathematics,
Vol. 11, 1973, pp. 351-359