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ACL
2004
15 years 7 months ago
Combining Acoustic and Pragmatic Features to Predict Recognition Performance in Spoken Dialogue Systems
We use machine learners trained on a combination of acoustic confidence and pragmatic plausibility features computed from dialogue context to predict the accuracy of incoming n-be...
Malte Gabsdil, Oliver Lemon
TWC
2008
85views more  TWC 2008»
15 years 6 months ago
Improved BDFE Using A Priori Information for Turbo Equalization
Abstract-- Turbo equalization improves communication system performance by iteratively exchanging information between soft-input soft-output (SISO) equalizer and SISO channel decod...
Jingxian Wu, Sang-Yick Leong, Kah-Ping Lee, Chengs...
EWMF
2003
Springer
15 years 11 months ago
Semantically Enhanced Collaborative Filtering on the Web
Item-based Collaborative Filtering (CF) algorithms have been designed to deal with the scalability problems associated with traditional user-based CF approaches without sacrificin...
Bamshad Mobasher, Xin Jin, Yanzan Zhou
QRE
2010
129views more  QRE 2010»
15 years 4 months ago
Improving quality of prediction in highly dynamic environments using approximate dynamic programming
In many applications, decision making under uncertainty often involves two steps- prediction of a certain quality parameter or indicator of the system under study and the subseque...
Rajesh Ganesan, Poornima Balakrishna, Lance Sherry
CEC
2005
IEEE
15 years 11 months ago
Evolving improved incremental learning schemes for neural network systems
It is well known that incremental learning can often be difficult for traditional neural network systems, due to newly learned information interfering with previously learned infor...
Tebogo Seipone, John A. Bullinaria