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TRECVID
2008
15 years 4 days ago
Learning TRECVID'08 High-Level Features from YouTube
Run No. Run ID Run Description infMAP (%) training on TV08 data 1 IUPR-TV-M SIFT visual words with maximum entropy 6.1 2 IUPR-TV-MF SIFT with maximum entropy, fused with color+tex...
Adrian Ulges, Christian Schulze, Markus Koch, Thom...
WWW
2009
ACM
15 years 11 months ago
Learning to recognize reliable users and content in social media with coupled mutual reinforcement
Community Question Answering (CQA) has emerged as a popular forum for users to pose questions for other users to answer. Over the last few years, CQA portals such as Naver and Yah...
Jiang Bian, Yandong Liu, Ding Zhou, Eugene Agichte...
ICRA
2010
IEEE
104views Robotics» more  ICRA 2010»
14 years 9 months ago
Using model knowledge for learning inverse dynamics
— In recent years, learning models from data has become an increasingly interesting tool for robotics, as it allows straightforward and accurate model approximation. However, in ...
Duy Nguyen-Tuong, Jan Peters
ICCV
2001
IEEE
16 years 19 days ago
Topology Free Hidden Markov Models: Application to Background Modeling
Hidden Markov Models (HMMs) are increasingly being used in computer vision for applications such as: gesture analysis, action recognition from video, and illumination modeling. Th...
Bjoern Stenger, Visvanathan Ramesh, Nikos Paragios...
KDD
2004
ACM
150views Data Mining» more  KDD 2004»
15 years 11 months ago
Markov Blankets and Meta-heuristics Search: Sentiment Extraction from Unstructured Texts
Extracting sentiments from unstructured text has emerged as an important problem in many disciplines. An accurate method would enable us, for example, to mine online opinions from ...
Edoardo Airoldi, Xue Bai, Rema Padman