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» Informed Selection of Training Examples for Knowledge Refine...
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AAAI
2000
13 years 8 months ago
Selective Sampling with Redundant Views
Selective sampling, a form of active learning, reduces the cost of labeling training data by asking only for the labels of the most informative unlabeled examples. We introduce a ...
Ion Muslea, Steven Minton, Craig A. Knoblock
EMNLP
2006
13 years 8 months ago
Unsupervised Information Extraction Approach Using Graph Mutual Reinforcement
Information Extraction (IE) is the task of extracting knowledge from unstructured text. We present a novel unsupervised approach for information extraction based on graph mutual r...
Hany Hassan, Ahmed Hassan, Ossama Emam
CVPR
2010
IEEE
14 years 3 months ago
Beyond Active Noun Tagging: Modeling Contextual Interactions for Multi-Class Active Learning
We present an active learning framework to simultaneously learn appearance and contextual models for scene understanding tasks (multi-class classification). Existing multi-class a...
Behjat Siddiquie, Abhinav Gupta
ICIP
2006
IEEE
14 years 9 months ago
Cover Selection for Steganographic Embedding
The primary goal of image steganography techniques has been to maximize embedding rate while minimizing the detectability of the resulting stego images against steganalysis techni...
Mehdi Kharrazi, Taha Taha Sencar, Nasir D. Memon
ICCV
2009
IEEE
13 years 5 months ago
Robust facial feature tracking using selected multi-resolution linear predictors
This paper proposes a learnt data-driven approach for accurate, real-time tracking of facial features using only intensity information. Constraints such as a-priori shape models o...
Eng-Jon Ong, Yuxuan Lan, Barry Theobald, Richard H...