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» Evaluating algorithms that learn from data streams
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CVPR
2010
IEEE
16 years 21 days ago
Learning from Interpolated Images using Neural Networks for Digital Forensics
Interpolated images have data redundancy, and special correlation exists among neighboring pixels, which is a crucial clue in digital forensics. We design a neural network based f...
Yizhen Huang, Na Fan
AIRS
2010
Springer
15 years 2 months ago
Semantic Relation Extraction Based on Semi-supervised Learning
Many tasks of information extraction or natural language processing have a property that the data naturally consist of several views--disjoint subsets of features. Specifically, a ...
Haibo Li, Yutaka Matsuo, Mitsuru Ishizuka
NIPS
2007
15 years 5 months ago
Active Preference Learning with Discrete Choice Data
We propose an active learning algorithm that learns a continuous valuation model from discrete preferences. The algorithm automatically decides what items are best presented to an...
Eric Brochu, Nando de Freitas, Abhijeet Ghosh
MM
2005
ACM
250views Multimedia» more  MM 2005»
15 years 10 months ago
An object-based video coding framework for video sequences obtained from static cameras
This paper presents a novel object-based video coding framework for videos obtained from a static camera. As opposed to most existing methods, the proposed method does not require...
Asaad Hakeem, Khurram Shafique, Mubarak Shah
PVLDB
2008
74views more  PVLDB 2008»
15 years 3 months ago
Out-of-order processing: a new architecture for high-performance stream systems
Many stream-processing systems enforce an order on data streams during query evaluation to help unblock blocking operators and purge state from stateful operators. Such in-order p...
Jin Li, Kristin Tufte, Vladislav Shkapenyuk, Vassi...