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STOC
2004
ACM
118views Algorithms» more  STOC 2004»
15 years 10 months ago
Boosted sampling: approximation algorithms for stochastic optimization
Several combinatorial optimization problems choose elements to minimize the total cost of constructing a feasible solution that satisfies requirements of clients. In the STEINER T...
Anupam Gupta, Martin Pál, R. Ravi, Amitabh ...
DAGSTUHL
2007
14 years 11 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
76
Voted
EMNLP
2007
14 years 11 months ago
Online Learning of Relaxed CCG Grammars for Parsing to Logical Form
We consider the problem of learning to parse sentences to lambda-calculus representations of their underlying semantics and present an algorithm that learns a weighted combinatory...
Luke S. Zettlemoyer, Michael Collins
ESA
2006
Springer
136views Algorithms» more  ESA 2006»
15 years 1 months ago
Approximation in Preemptive Stochastic Online Scheduling
Abstract. We present a first constant performance guarantee for preemptive stochastic scheduling to minimize the sum of weighted completion times. For scheduling jobs with release ...
Nicole Megow, Tjark Vredeveld
WINE
2009
Springer
178views Economy» more  WINE 2009»
15 years 4 months ago
Computing Optimal Contracts in Series-Parallel Heterogeneous Combinatorial Agencies
We study an economic setting in which a principal motivates a team of strategic agents to exert costly effort toward the success of a joint project. The action taken by each agent...
Yuval Emek, Michal Feldman