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SODA
2010
ACM
149views Algorithms» more  SODA 2010»
14 years 5 months ago
Sharp kernel clustering algorithms and their associated Grothendieck inequalities
abstract Subhash Khot Assaf Naor In the kernel clustering problem we are given a (large) n ? n symmetric positive semidefinite matrix A = (aij) with n i=1 n j=1 aij = 0 and a (sma...
Subhash Khot, Assaf Naor
SODA
2000
ACM
120views Algorithms» more  SODA 2000»
13 years 9 months ago
Minimum ratio canceling is oracle polynomial for linear programming, but not strongly polynomial, even for networks
This paper shows that the minimum ratio canceling algorithm of Wallacher (1989) (and a faster relaxed version) can be generalized to an algorithm for general linear programs with ...
S. Thomas McCormick, Akiyoshi Shioura
ALGORITHMICA
2004
130views more  ALGORITHMICA 2004»
13 years 7 months ago
The Power of Priority Algorithms for Facility Location and Set Cover
We apply and extend the priority algorithm framework introduced by Borodin, Nielsen, and Rackoff to define "greedy-like" algorithms for the (uncapacitated) facility locat...
Spyros Angelopoulos, Allan Borodin
COMPGEOM
2011
ACM
12 years 11 months ago
Comparing distributions and shapes using the kernel distance
Starting with a similarity function between objects, it is possible to define a distance metric (the kernel distance) on pairs of objects, and more generally on probability distr...
Sarang C. Joshi, Raj Varma Kommaraju, Jeff M. Phil...
NIPS
2007
13 years 9 months ago
What makes some POMDP problems easy to approximate?
Point-based algorithms have been surprisingly successful in computing approximately optimal solutions for partially observable Markov decision processes (POMDPs) in high dimension...
David Hsu, Wee Sun Lee, Nan Rong