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ML
2000
ACM
154views Machine Learning» more  ML 2000»
15 years 6 months ago
Lazy Learning of Bayesian Rules
The naive Bayesian classifier provides a simple and effective approach to classifier learning, but its attribute independence assumption is often violated in the real world. A numb...
Zijian Zheng, Geoffrey I. Webb
JUCS
2010
114views more  JUCS 2010»
15 years 1 months ago
On Reliable Platform Configuration Change Reporting Mechanisms for Trusted Computing Enabled Platforms
: One of the most important use-cases of Trusted Computing is Remote Attestation. It allows platforms to get a trustworthy proof of the loaded software and current configuration of...
Kurt Dietrich
ICCV
2009
IEEE
16 years 11 months ago
Semi-Supervised Random Forests
Random Forests (RFs) have become commonplace in many computer vision applications. Their popularity is mainly driven by their high computational efficiency during both training ...
Christian Leistner, Amir Saffari, Jakob Santner, H...
ICCV
2009
IEEE
16 years 11 months ago
Weakly supervised discriminative localization and classification: a joint learning process
Visual categorization problems, such as object classification or action recognition, are increasingly often approached using a detection strategy: a classifier function is first ...
Minh Hoai Nguyen, Lorenzo Torresani, Fernando de l...
CVPR
2005
IEEE
16 years 8 months ago
Unsupervised Learning of Discriminative Edge Measures for Vehicle Matching between Non-Overlapping Cameras
This paper proposes a novel method for matching road vehicles between two non-overlapping cameras. The matching problem is formulated as a same-different classification problem: p...
Ying Shan, Harpreet S. Sawhney, Rakesh Kumar