May 31, 2024 at 6:00PM
Abstract
Classical data structures are designed to minimize the cost of each operation. In many situations this is too restrictive a goal: All we need is that the total cost of a sequence of operations is small. Using this more relaxed objective allows the design of simlper data structures that adapt to the way they are used. I’ll give some examples and discuss a framework for the design and analysis of such structures.
Bio
Robert E. Tarjan, the James S. McDonnell Distinguished University Professor of Computer Science, joined Princeton in 1985. He received doctoral and master’s degrees in computer science from Stanford in 1972 and 1971, respectively, after earning a bachelor’s in mathematics from Caltech. His academic experience involved assistant professorships at Cornell and Stanford, and a Miller research fellowship at UC, Berkeley. Professor Tarjan’s extensive involvement in the private sector includes past and continuing fellowship, research and scientific roles at the NEC Research Institute, Princeton; InterTrust Technologies, Sunnyvale, CA; Compaq Computer, Houston, TX; Hewlett-Packard, Palo Alto, CA; and Microsoft, Mountain View, CA. His honors include Caltech’s Distinguished Alumni Award in 2010, the 2009 Edelman Award from INFORMS (member of winning H-P team), fellow of the Society for Industrial and Applied Mathematics (2009), and the Blaise Pascal Medal in Mathematics and Computer Science from the European Academy of Sciences in 2004. Professor Tarjan was the first winner of the Rolf Nevanlinna Prize, established in 1982 and awarded every four years for outstanding contributions in mathematical aspects of information sciences by the International Mathematical Union.