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SIGIR
2012
ACM
12 years 14 days ago
Active query selection for learning rankers
Methods that reduce the amount of labeled data needed for training have focused more on selecting which documents to label than on which queries should be labeled. One exception t...
Mustafa Bilgic, Paul N. Bennett
ICPR
2010
IEEE
14 years 3 months ago
Motif Discovery and Feature Selection for CRF-Based Activity Recognition
Abstract—Due to their ability to model sequential data without making unnecessary independence assumptions, conditional random fields (CRFs) have become an increasingly popular ...
Liyue Zhao, Xi Wang, Gita Sukthankar
ICCV
2011
IEEE
12 years 10 months ago
Actively Selecting Annotations Among Objects and Attributes
We present an active learning approach to choose image annotation requests among both object category labels and the objects’ attribute labels. The goal is to solicit those labe...
Adriana Kovashka, Sudheendra Vijayanarasimhan, Kri...
ICCV
2003
IEEE
14 years 12 months ago
Conditional Feature Sensitivity: A Unifying View on Active Recognition and Feature Selection
The objective of active recognition is to iteratively collect the next "best" measurements (e.g., camera angles or viewpoints), to maximally reduce ambiguities in recogn...
Xiang Sean Zhou, Dorin Comaniciu, Arun Krishnan
PAMI
2002
124views more  PAMI 2002»
13 years 9 months ago
Information Theoretic Sensor Data Selection for Active Object Recognition and State Estimation
We introduce a formalism for optimal sensor parameter selection for iterative state estimation in static systems. Our optimality criterion is the reduction of uncertainty in the st...
Joachim Denzler, Christopher M. Brown