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» A Multi-Resolution Relational Data Model
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IJCAI
2007
13 years 10 months ago
A Theoretical Framework for Learning Bayesian Networks with Parameter Inequality Constraints
The task of learning models for many real-world problems requires incorporating domain knowledge into learning algorithms, to enable accurate learning from a realistic volume of t...
Radu Stefan Niculescu, Tom M. Mitchell, R. Bharat ...
IJCAI
2007
13 years 10 months ago
Compiling Bayesian Networks by Symbolic Probability Calculation Based on Zero-Suppressed BDDs
Compiling Bayesian networks (BNs) is one of the hot topics in the area of probabilistic modeling and processing. In this paper, we propose a new method of compiling BNs into multi...
Shin-ichi Minato, Ken Satoh, Taisuke Sato
IM
2007
13 years 10 months ago
Capacity and Performance Overhead in Dynamic Resource Allocation to Virtual Containers
—Today’s enterprise data centers are shifting towards a utility computing model where many business critical applications share a common pool of infrastructure resources that o...
Zhikui Wang, Xiaoyun Zhu, Pradeep Padala, Sharad S...
NIPS
2008
13 years 10 months ago
Inferring rankings under constrained sensing
Motivated by applications like elections, web-page ranking, revenue maximization etc., we consider the question of inferring popular rankings using constrained data. More specific...
Srikanth Jagabathula, Devavrat Shah
NIPS
2008
13 years 10 months ago
Multi-Level Active Prediction of Useful Image Annotations for Recognition
We introduce a framework for actively learning visual categories from a mixture of weakly and strongly labeled image examples. We propose to allow the categorylearner to strategic...
Sudheendra Vijayanarasimhan, Kristen Grauman