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» Learning Partially Observable Action Models: Efficient Algor...
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120
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AI
2011
Springer
14 years 9 months ago
First-order logical filtering
Logical filtering is the process of updating a belief state (set of possible world states) after a sequence of executed actions and perceived observations. In general, it is intr...
Afsaneh Shirazi, Eyal Amir
125
Voted
ICML
2009
IEEE
16 years 3 months ago
Bayesian inference for Plackett-Luce ranking models
This paper gives an efficient Bayesian method for inferring the parameters of a PlackettLuce ranking model. Such models are parameterised distributions over rankings of a finite s...
John Guiver, Edward Snelson
ICML
2007
IEEE
16 years 3 months ago
Kernelizing PLS, degrees of freedom, and efficient model selection
Kernelizing partial least squares (PLS), an algorithm which has been particularly popular in chemometrics, leads to kernel PLS which has several interesting properties, including ...
Mikio L. Braun, Nicole Krämer
AI
1998
Springer
15 years 6 months ago
Sequential Instance-Based Learning
This paper presents and evaluates sequential instance-based learning (SIBL), an approach to action selection based upon data gleaned from prior problem solving experiences. SIBL le...
Susan L. Epstein, Jenngang Shih
169
Voted
NAACL
2010
15 years 14 days ago
An Efficient Algorithm for Easy-First Non-Directional Dependency Parsing
We present a novel deterministic dependency parsing algorithm that attempts to create the easiest arcs in the dependency structure first in a non-directional manner. Traditional d...
Yoav Goldberg, Michael Elhadad