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NIPS
1998
14 years 7 days ago
Risk Sensitive Reinforcement Learning
In this paper, we consider Markov Decision Processes (MDPs) with error states. Error states are those states entering which is undesirable or dangerous. We define the risk with re...
Ralph Neuneier, Oliver Mihatsch
COLING
1996
14 years 6 days ago
Computational Complexity of Probabilistic Disambiguation by means of Tree-Grammars
This paper studies the computational complexity of disambiguation under probabilistic tree-grammars as in (Bod, 1992; Schabes and Waters, 1993). It presents a proof that the follo...
Khalil Sima'an
ESA
2010
Springer
246views Algorithms» more  ESA 2010»
14 years 2 hour ago
Estimating the Average of a Lipschitz-Continuous Function from One Sample
We study the problem of estimating the average of a Lipschitz continuous function f defined over a metric space, by querying f at only a single point. More specifically, we explore...
Abhimanyu Das, David Kempe
PR
2006
164views more  PR 2006»
13 years 10 months ago
Locally linear metric adaptation with application to semi-supervised clustering and image retrieval
Many computer vision and pattern recognition algorithms are very sensitive to the choice of an appropriate distance metric. Some recent research sought to address a variant of the...
Hong Chang, Dit-Yan Yeung
TELSYS
2008
85views more  TELSYS 2008»
13 years 10 months ago
Trustworthy Web services provisioning for differentiated customer services
With the number of e-Business applications dramatically increasing, a service level agreement (SLA) will play an important part in Web services. The SLA is a combination of severa...
Kaiqi Xiong, Harry G. Perros