A model of computation for MapReduce
- H. Karloff, Siddharth Suri, Sergei Vassilvitskii
- Computer ScienceACM-SIAM Symposium on Discrete Algorithms
- 17 January 2010
A simulation lemma is proved showing that a large class of PRAM algorithms can be efficiently simulated via MapReduce, and it is demonstrated how algorithms can take advantage of this fact to compute an MST of a dense graph in only two rounds.
Algebraic methods for interactive proof systems
- C. Lund, L. Fortnow, H. Karloff, N. Nisan
- Computer ScienceProceedings [] 31st Annual Symposium on…
- 22 October 1990
The technique is used to prove that every language in the polynomial-time hierarchy has an interactive proof system and has implications for program checking, verification, and self-correction.
Combining geometry and combinatorics: A unified approach to sparse signal recovery
- R. Berinde, A. Gilbert, P. Indyk, H. Karloff, M. Strauss
- Computer Science, Mathematics46th Annual Allerton Conference on Communication…
- 29 April 2008
A unification of geometric and combinatorial approaches to sparse signal recovery is presented, which results in new measurement matrix constructions and algorithms for signal recovery which are superior in either the number of measurements or computational efficiency of decoders.
A 7/8-approximation algorithm for MAX 3SAT?
- H. Karloff, U. Zwick
- Computer ScienceProceedings 38th Annual Symposium on Foundations…
- 19 October 1997
A randomized approximation algorithm which takes an instance of MAX 3SAT as input that is optimal if the instance-a collection of clauses each of length at most three-is satisfiable, and a method of obtaining direct semidefinite relaxations of any constraint satisfaction problem of the form MAX CSP(F), where F is a finite family of Boolean functions.
An improved approximation algorithm for multiway cut
- G. Călinescu, H. Karloff, Y. Rabani
- Computer ScienceSymposium on the Theory of Computing
- 23 May 1998
A new linear programming relaxation for Multiway Cut is presented and a new approximation algorithm based on it achieves a performance ratio of at most 1.5?1k, which improves the previous result for every value of k.
New results on server problems
- M. Chrobak, H. Karloff, T. H. Payne, S. Vishwanathan
- Computer ScienceACM-SIAM Symposium on Discrete Algorithms
- 1 March 1991
A fast algorithm for oflline computing of an optimal schedule is given, and it is shown that finding an optimal offline schedule is at least as hard as the assignment problem.
Approximation algorithms for the 0-extension problem
- G. Călinescu, H. Karloff, Y. Rabani
- Mathematics, Computer ScienceACM-SIAM Symposium on Discrete Algorithms
- 9 January 2001
It is proved that the integrality ratio of the metric relaxation is at least c√lgk for a positive c for infinitely many k and the results improve some of the results of Kleinberg and Tardos and they further the understanding on how to use metric relaxations.
New algorithms for an ancient scheduling problem
- Y. Bartal, A. Fiat, H. Karloff, R. Vohra
- Computer ScienceSymposium on the Theory of Computing
- 1 July 1992
To the best of the knowledge, this 4/3-competitive algorithm is the first specifically randomized algorithm for the original, original, on-line scheduling problem, and probably the first directly randomized algorithm of its kind.
On generating near-optimal tableaux for conditional functional dependencies
- Lukasz Golab, H. Karloff, Flip Korn, D. Srivastava, Bei Yu
- Computer ScienceProceedings of the VLDB Endowment
- 1 August 2008
This paper is the first to formally characterize a "good" pattern tableau, based on naturally desirable properties of support, confidence and parsimony, and shows that the problem of generating an optimal tableau for a given FD is NP-complete but can be approximated in polynomial time via a greedy algorithm.
Lower bounds for linear locally decodable codes and private information retrieval
- Oded Goldreich, H. Karloff, L. Schulman, L. Trevisan
- Computer ScienceProceedings 17th IEEE Annual Conference on…
- 21 May 2002
It is shown a reduction from the complexity of one-round, information-theoretic Private Information Retrieval Systems (with two servers) to Locally Decodable Codes, and it is proved that if all the servers’ answers are linear combinations of the database content, then t = Ω (n/2a), where t is the length of the user’s query.
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