AMS Sectional Meeting Program by Special Session
Current as of Tuesday, April 12, 2005 15:08:52
1991 Central Section Meeting
Fargo, ND, October 25-26, 1991
Andy R Magid, AMS firstname.lastname@example.org
Special Session on Constrained Approximation, Theory and Algorithms
Friday October 25, 1991, 2:30 p.m.-5:20 p.m.
Special Session on Constrained Approximation, Theory and Algorithms, I
Family Life Center, Room 124, Memorial Union
Constrained best approximation.
Frank Deutsch*, Pennsylvania State University, University Park
Recent progress in constrained approximation.
Joseph Ward*, Texas A\thsp\&\thsp M University, College Station
A family of natural best L_1-approximants by nondecreasing functions.
David A. Legg, Indiana University-Purdue University, Ft.\ Wayne
Douglas W. Townsend*, Indiana University-Purdue University, Ft.\ Wayne
Strong uniqueness and simultaneous approximation.
Alan Egger, Idaho State University
Robert Huotari*, Idaho State University
Salem M. Sahab, King Abdulaziz University, Saudi Arabia
Constrained L_p-approximation by generalized convex functions.
Vasant A. Ubhaya, North Dakota State University, Fargo
Yuesheng Xu*, North Dakota State University, Fargo
Best interpolation in a strip.
A. L. Dontchev*, Mathematical Reviews, Ann Arbor, Michigan
- 2:30 p.m.
Saturday October 26, 1991, 2:00 p.m.-4:50 p.m.
Special Session on Constrained Approximation, Theory and Algorithms, II
Family Life Center, Room 319, Memorial Union
Constrained approximation at IMSL.
Philip Smith*, International Mathematical Statistics Library Incorporated, Houston, Texas
The Newton method for convex regression, data smoothing, and quadratic programming with bounded constraints.
Wu Li, Old Dominion University
John Swetits*, Old Dominion University
Estimation and approximation using infinite dimensional convex programs with entropy type objectives.
Jonathan M. Borwein*, University of Waterloo
A convex programming approach to constrained approximation.
Jon Borwein, University of Waterloo
Adrian Lewis*, University of Waterloo
Active set algorithms for isotonic regression.
Michael J. Best*, University of Waterloo
Generalized convex functions and best L_p approximation.
Ronald M. Mathsen, North Dakota State University, Fargo
Vasant A. Ubhaya*, North Dakota State University, Fargo
- 2:00 p.m.