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» Structure learning of Bayesian networks using constraints
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ICDM
2007
IEEE
162views Data Mining» more  ICDM 2007»
15 years 8 months ago
Exploiting Network Structure for Active Inference in Collective Classification
Active inference seeks to maximize classification performance while minimizing the amount of data that must be labeled ex ante. This task is particularly relevant in the context o...
Matthew J. Rattigan, Marc Maier, David Jensen, Bin...
JMLR
2006
153views more  JMLR 2006»
15 years 4 months ago
Collaborative Multiagent Reinforcement Learning by Payoff Propagation
In this article we describe a set of scalable techniques for learning the behavior of a group of agents in a collaborative multiagent setting. As a basis we use the framework of c...
Jelle R. Kok, Nikos A. Vlassis
CVPR
2009
IEEE
17 years 13 hour ago
Recognizing Linked Events: Searching the Space of Feasible Explanations
The ambiguity inherent in a localized analysis of events from video can be resolved by exploiting constraints between events and examining only feasible global explanations. We sho...
Dima Damen (University of Leeds), David Hogg (Univ...
CVPR
2012
IEEE
13 years 6 months ago
Sum-product networks for modeling activities with stochastic structure
This paper addresses recognition of human activities with stochastic structure, characterized by variable spacetime arrangements of primitive actions, and conducted by a variable ...
Mohamed R. Amer, Sinisa Todorovic
ETS
2000
IEEE
193views Hardware» more  ETS 2000»
15 years 4 months ago
The Virtual School: An integrated collaborative environment for the classroom
A significant opportunity presented by the availability of high-speed network access in the classroom is the ability to collaborate with remote students and mentors. To be success...
Philip L. Isenhour, John M. Carroll, Dennis C. Nea...