Amortized efficiency of list update and paging rules
Communications of the ACM
STOC '94 Proceedings of the twenty-sixth annual ACM symposium on Theory of computing
Approximation algorithms for NP-hard problems
Approximation algorithms for NP-hard problems
Improved performance of the greedy algorithm for partial cover
Information Processing Letters
Online computation and competitive analysis
Online computation and competitive analysis
Algorithms for facility location problems with outliers
SODA '01 Proceedings of the twelfth annual ACM-SIAM symposium on Discrete algorithms
Approximation algorithms
Faster approximation algorithms for the minimum latency problem
SODA '03 Proceedings of the fourteenth annual ACM-SIAM symposium on Discrete algorithms
Developments from a June 1996 seminar on Online algorithms: the state of the art
Developments from a June 1996 seminar on Online algorithms: the state of the art
STACS '98 Proceedings of the 15th Annual Symposium on Theoretical Aspects of Computer Science
The t-Vertex Cover Problem: Extending the Half Integrality Framework with Budget Constraints
APPROX '98 Proceedings of the International Workshop on Approximation Algorithms for Combinatorial Optimization
Improved Approximation Algorithms for Metric Facility Location Problems
APPROX '02 Proceedings of the 5th International Workshop on Approximation Algorithms for Combinatorial Optimization
SIAM Journal on Computing
Approximation algorithms for hierarchical location problems
Proceedings of the thirty-fifth annual ACM symposium on Theory of computing
Greedy facility location algorithms analyzed using dual fitting with factor-revealing LP
Journal of the ACM (JACM)
Local Search Heuristics for k-Median and Facility Location Problems
SIAM Journal on Computing
SODA '04 Proceedings of the fifteenth annual ACM-SIAM symposium on Discrete algorithms
Approximation algorithms for a hierarchically structured bin packing problem
Information Processing Letters
Boosted sampling: approximation algorithms for stochastic optimization
STOC '04 Proceedings of the thirty-sixth annual ACM symposium on Theory of computing
Incremental Clustering and Dynamic Information Retrieval
SIAM Journal on Computing
Approximating the Stochastic Knapsack Problem: The Benefit of Adaptivity
FOCS '04 Proceedings of the 45th Annual IEEE Symposium on Foundations of Computer Science
An Edge in Time Saves Nine: LP Rounding Approximation Algorithms for Stochastic Network Design
FOCS '04 Proceedings of the 45th Annual IEEE Symposium on Foundations of Computer Science
Universal approximations for TSP, Steiner tree, and set cover
Proceedings of the thirty-seventh annual ACM symposium on Theory of computing
Saving an epsilon: a 2-approximation for the k-MST problem in graphs
Proceedings of the thirty-seventh annual ACM symposium on Theory of computing
Performance guarantees for hierarchical clustering
Journal of Computer and System Sciences - Special issue on COLT 2002
The reverse greedy algorithm for the metric K-median problem
COCOON'05 Proceedings of the 11th annual international conference on Computing and Combinatorics
A primal-dual approximation algorithm for partial vertex cover: making educated guesses
APPROX'05/RANDOM'05 Proceedings of the 8th international workshop on Approximation, Randomization and Combinatorial Optimization Problems, and Proceedings of the 9th international conference on Randamization and Computation: algorithms and techniques
A plant location guide for the unsure
Proceedings of the nineteenth annual ACM-SIAM symposium on Discrete algorithms
An Optimal Incremental Algorithm for Minimizing Lateness with Rejection
ESA '08 Proceedings of the 16th annual European symposium on Algorithms
A Plant Location Guide for the Unsure: Approximation Algorithms for Min-Max Location Problems
Mathematics of Operations Research
Better bounds for incremental medians
WAOA'07 Proceedings of the 5th international conference on Approximation and online algorithms
Randomized algorithms for online bounded bidding
Information Processing Letters
Incremental Facility Location Problem and Its Competitive Algorithms
Journal of Combinatorial Optimization
Some results on incremental vertex cover problem
AAIM'10 Proceedings of the 6th international conference on Algorithmic aspects in information and management
Better bounds for incremental medians
Theoretical Computer Science
An improved competitive algorithm for one-dimensional incremental median problem
FAW-AAIM'11 Proceedings of the 5th joint international frontiers in algorithmics, and 7th international conference on Algorithmic aspects in information and management
An incremental model for combinatorial maximization problems
WEA'06 Proceedings of the 5th international conference on Experimental Algorithms
On hierarchical diameter-clustering, and the supplier problem
WAOA'06 Proceedings of the 4th international conference on Approximation and Online Algorithms
Oblivious medians via online bidding
LATIN'06 Proceedings of the 7th Latin American conference on Theoretical Informatics
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We present a general framework and algorithmic approach for incremental approximation algorithms. The framework handles cardinality constrained minimization problems, such as the k-median and k-MST problems. Given some notion of ordering on solutions of different cardinalities k, we give solutions for all values of k such that the solutions respect the ordering and such that for any k, our solution is close in value to the value of an optimal solution of cardinality k. For instance, for the k-median problem, the notion of ordering is set inclusion and our incremental algorithm produces solutions such that any k and k', k , our solution of size k is a subset of our solution of size k'. We show that our framework applies to this incremental version of the k-median problem (introduced by Mettu and Plaxton [30]), and incremental versions of the k-MST problem, k-vertex cover problem, k-set cover problem, as well as the uncapacitated facility location problem (which is not cardinality-constrained). For these problems we either get new incremental algorithms, or improvements over what was previously known. We also show that the framework applies to hierarchical clustering problems. In particular, we give an improved algorithm for a hierarchical version of the k-median problem introduced by Plaxton [31].