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IJCAI
2007
15 years 1 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
15 years 1 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
15 years 1 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
15 years 1 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
15 years 1 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