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AAAI
2011
14 years 6 months ago
Mean Field Inference in Dependency Networks: An Empirical Study
Dependency networks are a compelling alternative to Bayesian networks for learning joint probability distributions from data and using them to compute probabilities. A dependency ...
Daniel Lowd, Arash Shamaei
ECCV
2006
Springer
16 years 8 months ago
Learning to Detect Objects of Many Classes Using Binary Classifiers
Viola and Jones [VJ] demonstrate that cascade classification methods can successfully detect objects belonging to a single class, such as faces. Detecting and identifying objects t...
Ramana Isukapalli, Ahmed M. Elgammal, Russell Grei...
WWW
2008
ACM
16 years 7 months ago
Learning multiple graphs for document recommendations
The Web offers rich relational data with different semantics. In this paper, we address the problem of document recommendation in a digital library, where the documents in questio...
Ding Zhou, Shenghuo Zhu, Kai Yu, Xiaodan Song, Bel...
FLAIRS
2007
15 years 9 months ago
Explaining Task Processing in Cognitive Assistants that Learn
As personal assistant software matures and assumes more autonomous control of its users’ activities, it becomes more critical that this software can explain its task processing....
Deborah L. McGuinness, Alyssa Glass, Michael Wolve...
NIPS
2007
15 years 8 months ago
Managing Power Consumption and Performance of Computing Systems Using Reinforcement Learning
Electrical power management in large-scale IT systems such as commercial datacenters is an application area of rapidly growing interest from both an economic and ecological perspe...
Gerald Tesauro, Rajarshi Das, Hoi Chan, Jeffrey O....