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AAAI
2010
13 years 6 months ago
Can Approximation Circumvent Gibbard-Satterthwaite?
The Gibbard-Satterthwaite Theorem asserts that any reasonable voting rule cannot be strategyproof. A large body of research in AI deals with circumventing this theorem via computa...
Ariel D. Procaccia
CORR
2011
Springer
192views Education» more  CORR 2011»
12 years 11 months ago
Improved Approximation Guarantees for Lower-Bounded Facility Location
d Abstract) Sara Ahmadian∗ Chaitanya Swamy∗ We consider the lower-bounded facility location (LBFL) problem (also sometimes called load-balanced facility location), which is a ...
Sara Ahmadian, Chaitanya Swamy
JMLR
2002
115views more  JMLR 2002»
13 years 4 months ago
PAC-Bayesian Generalisation Error Bounds for Gaussian Process Classification
Approximate Bayesian Gaussian process (GP) classification techniques are powerful nonparametric learning methods, similar in appearance and performance to support vector machines....
Matthias Seeger
EACL
2006
ACL Anthology
13 years 6 months ago
Online Learning of Approximate Dependency Parsing Algorithms
In this paper we extend the maximum spanning tree (MST) dependency parsing framework of McDonald et al. (2005c) to incorporate higher-order feature representations and allow depen...
Ryan T. McDonald, Fernando C. N. Pereira
ICML
2005
IEEE
14 years 5 months ago
Learning approximate preconditions for methods in hierarchical plans
A significant challenge in developing planning systems for practical applications is the difficulty of acquiring the domain knowledge needed by such systems. One method for acquir...
Dana S. Nau, David W. Aha, Héctor Muñ...