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134
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JMLR
2002
111views more  JMLR 2002»
15 years 1 months ago
The Learning-Curve Sampling Method Applied to Model-Based Clustering
We examine the learning-curve sampling method, an approach for applying machinelearning algorithms to large data sets. The approach is based on the observation that the computatio...
Christopher Meek, Bo Thiesson, David Heckerman
SIAMCO
2010
93views more  SIAMCO 2010»
15 years 6 days ago
Dynamic Vehicle Routing with Priority Classes of Stochastic Demands
In this paper we introduce a dynamic vehicle routing problem in which there are multiple vehicles and multiple priority classes of service demands. Service demands of each priority...
Stephen L. Smith, Marco Pavone, Francesco Bullo, E...
124
Voted
CVPR
2004
IEEE
16 years 3 months ago
Learning a Restricted Bayesian Network for Object Detection
Many classes of images have the characteristics of sparse structuring of statistical dependency and the presence of conditional independencies among various groups of variables. S...
Henry Schneiderman
ICFP
2009
ACM
16 years 2 months ago
Parallel concurrent ML
Concurrent ML (CML) is a high-level message-passing language that supports the construction of first-class synchronous abstractions called events. This mechanism has proven quite ...
John H. Reppy, Claudio V. Russo, Yingqi Xiao
115
Voted
STOC
2005
ACM
112views Algorithms» more  STOC 2005»
16 years 2 months ago
The complexity of agreement
A celebrated 1976 theorem of Aumann asserts that honest, rational Bayesian agents with common priors will never "agree to disagree": if their opinions about any topic ar...
Scott Aaronson