The Hypertext Bibliography Project at MIT also includes listings of my FOCS papers.
The FOCS and Positano versions of this paper merged my results on a dynamic program used for RNA secondary structure prediction, with Raffaele's on sequence comparison. The Bethesda talk and the TR version both used the longer title "Speeding up dynamic programming with application to the computation of RNA structure", and included only the RNA result, which used a mild convexity assumption on certain costs to save two orders of magnitude in total time. This work incited a boom in computational biology within the theory community that is still going strong. But the RNA results were quickly improved by a log factor [Aggarwal et al. at the same FOCS] and never made it into a journal paper.
(Bibtex: Positano, FOCS -- Citations -- Citations of "Efficient algorithms..." -- MIT hypertext bibliography -- CiteSeer)
Uses quadtrees to construct triangulations with extra Steiner vertices added to the original input. Triangulates planar point sets and polygons, with all angles bounded away from zero, using a number of triangles within a constant of optimal. Triangulates planar point sets with all angles non-obtuse, using linearly many triangles. Triangulates higher dimensional point sets with no small solid angles and a number of simplices within a constant of optimal. Augments any higher dimensional point set so the Delaunay triangulation has linear complexity.
(BibTeX -- Citations -- Preliminary copy of journal version -- MIT hypertext bibliography -- CiteSeer -- ACM DL (JCSS))
Uses Dobkin-Kirkpatrick hierarchies to perform linear programming queries in the intersection of several convex polyhedra. By maintaining a collection of halfspaces as several subsets, represented by polyhedra, this leads to algorithms for a dynamic linear program in which updates change the set of constraints. The fully dynamic results have largely been subsumed by Agarwal and Matoušek, but this paper also includes polylog time results for semi-online problems, and uses them to give a fast randomized algorithm for the planar 2-center problem (later improved by various authors, most recently in "Faster Construction of Planar Two-Centers", which re-uses the data structures described here).
(BibTeX -- Citations -- CiteSeer -- ACM DL)
This conference paper merged my results from "Dynamic Euclidean minimum spanning trees" with results of my co-authors on nearest neighbors and halfspace range searching.
Uses a divide and conquer on the edge set of a graph, together with the idea of replacing subgraphs by sparser certificates, to make various dynamic algorithms as fast on dense graphs as they are on sparse graphs. Applications include random generation of spanning trees as well as finding the k minimum weight spanning trees for a given parameter k.
(BibTeX -- Citations -- MIT hypertext bibliography -- ACM DL)
Finds multiple short paths connecting two terminals in a graph (allowing repeated vertices and edges in the paths) in constant time per path after a preprocessing stage dominated by a single-source shortest path computation. Applications include dynamic programs for the knapsack problem, biological sequence alignment, and maximum inscribed polygons.
(BibTeX -- Full paper -- Citations -- Graehl implementation -- Jiménez-Marzal implementations -- Shibuya implementation -- Martins implementation -- CiteSeer: TR '94, SJC '98 -- ACM DL)
Speeds up 3-coloring by solving a harder problem: constraint satisfaction in which each variable can take on one of three values and each constraint forbids a pair of variable assignments. The detailed solution involves several long hairy case analyses. Similar methods apply also to 3-list-coloring, 3-edge-coloring, and 3-SAT. The 3-SAT algorithm is fixed-parameter tractible in that it is polynomial time when the number of 3-variable clauses is O(log n). Merged into 3-coloring in time O(1.3289^n) for the journal version.
(BibTeX -- Citations -- DIMACS abstract and slides -- CiteSeer)
We describe algorithms for maintaining the minimum spanning tree in a graph in which the edge weights are piecewise linear functions of time that may change unpredictably. We solve the problem in time O(n2/3 polylog n) per combinatorial change to the tree for general graphs, and in time O(n1/4 polylog n) per combinatorial change to the tree for planar graphs.
(BibTeX -- FOCS '98 talk slides -- Citations -- CiteSeer -- ACM DL)
We introduce a class of "inverse parametric optimization" problems, in which one is given both a parametric optimization problem and a desired optimal solution; the task is to determine parameter values that lead to the given solution. We use low-dimensional linear programming and geometric sampling techniques to solve such problems for minimum spanning trees, shortest paths, and other optimal subgraph problems, and discuss applications in multicast routing, vehicle path planning, resource allocation, and board game programming.
(BibTeX -- Citations -- ACM DL (FOCS) -- ACM DL (SJC))
Conferences -- Publications -- David Eppstein -- Theory Group -- Inf. & Comp. Sci. -- UC Irvine
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