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AAAI
2012
13 years 2 months ago
An Object-Based Bayesian Framework for Top-Down Visual Attention
We introduce a new task-independent framework to model top-down overt visual attention based on graphical models for probabilistic inference and reasoning. We describe a Dynamic B...
Ali Borji, Dicky N. Sihite, Laurent Itti
AMAI
2004
Springer
15 years 5 months ago
Using the Central Limit Theorem for Belief Network Learning
Learning the parameters (conditional and marginal probabilities) from a data set is a common method of building a belief network. Consider the situation where we have known graph s...
Ian Davidson, Minoo Aminian
113
Voted
IAT
2009
IEEE
15 years 6 months ago
Cluster-Swap: A Distributed K-median Algorithm for Sensor Networks
In building practical sensor networks, it is often beneficial to use only a subset of sensors to take measurements because of computational, communication, and power limitations....
Yoonheui Kim, Victor R. Lesser, Deepak Ganesan, Ra...
ISCC
2006
IEEE
188views Communications» more  ISCC 2006»
15 years 5 months ago
Active Learning Driven Data Acquisition for Sensor Networks
Online monitoring of a physical phenomenon over a geographical area is a popular application of sensor networks. Networks representative of this class of applications are typicall...
Anish Muttreja, Anand Raghunathan, Srivaths Ravi, ...
AUSDM
2007
Springer
185views Data Mining» more  AUSDM 2007»
15 years 6 months ago
An Approach to Argumentation Context Mining from Dialogue History in an E-Market Scenario
Argumentation allows agents to exchange additional information to argue about their beliefs and other mental attitudes during the negotiation process. Utterances and subsequent obs...
Khandaker Shahidul Islam