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» Learning Models for Predicting Recognition Performance
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UCS
2007
Springer
15 years 3 months ago
Discriminative Temporal Smoothing for Activity Recognition from Wearable Sensors
Abstract. This paper describes daily life activity recognition using wearable acceleration sensors attached to four different parts of the human body. The experimental data set con...
Jaakko Suutala, Susanna Pirttikangas, Juha Rö...
UAI
2004
14 years 11 months ago
A Bayesian Approach toward Active Learning for Collaborative Filtering
Collaborative filtering is a useful technique for exploiting the preference patterns of a group of users to predict the utility of items for the active user. In general, the perfo...
Rong Jin, Luo Si
ICASSP
2011
IEEE
14 years 1 months ago
A multi-stream ASR framework for BLSTM modeling of conversational speech
We propose a novel multi-stream framework for continuous conversational speech recognition which employs bidirectional Long Short-Term Memory (BLSTM) networks for phoneme predicti...
Martin Wöllmer, Florian Eyben, Björn Sch...
EMNLP
2008
14 years 11 months ago
Unsupervised Multilingual Learning for POS Tagging
We demonstrate the effectiveness of multilingual learning for unsupervised part-of-speech tagging. The key hypothesis of multilingual learning is that by combining cues from multi...
Benjamin Snyder, Tahira Naseem, Jacob Eisenstein, ...
CVPR
2007
IEEE
15 years 12 months ago
Discriminant Additive Tangent Spaces for Object Recognition
Pattern variation is a major factor that affects the performance of recognition systems. In this paper, a novel manifold tangent modeling method called Discriminant Additive Tange...
Liang Xiong, Jianguo Li, Changshui Zhang