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DAGSTUHL
2007
13 years 10 months ago
Sampling-based Approximation Algorithms for Multi-stage Stochastic Optimization
Stochastic optimization problems provide a means to model uncertainty in the input data where the uncertainty is modeled by a probability distribution over the possible realizatio...
Chaitanya Swamy, David B. Shmoys
SODA
2001
ACM
166views Algorithms» more  SODA 2001»
13 years 10 months ago
Better approximation algorithms for bin covering
Bin covering takes as input a list of items with sizes in (0 1) and places them into bins of unit demand so as to maximize the number of bins whose demand is satis ed. This is in ...
János Csirik, David S. Johnson, Claire Keny...
DAM
1999
169views more  DAM 1999»
13 years 8 months ago
Approximating the Weight of Shallow Steiner Trees
This paper deals with the problem of constructing Steiner trees of minimum weight with diameter bounded by d, spanning a given set of vertices in a graph. Exact solutions or logar...
Guy Kortsarz, David Peleg
AUTOMATICA
2008
107views more  AUTOMATICA 2008»
13 years 8 months ago
New algorithms of the Q-learning type
We propose two algorithms for Q-learning that use the two-timescale stochastic approximation methodology. The first of these updates Q-values of all feasible state
Shalabh Bhatnagar, K. Mohan Babu
JAL
2002
71views more  JAL 2002»
13 years 8 months ago
A primal-dual schema based approximation algorithm for the element connectivity problem
The element connectivity problem falls in the category of survivable network design problems { it is intermediate to the versions that ask for edge-disjoint and vertex-disjoint pa...
Kamal Jain, Ion I. Mandoiu, Vijay V. Vazirani, Dav...