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SIGIR
2011
ACM
12 years 11 months ago
Collaborative competitive filtering: learning recommender using context of user choice
While a user’s preference is directly reflected in the interactive choice process between her and the recommender, this wealth of information was not fully exploited for learni...
Shuang-Hong Yang, Bo Long, Alexander J. Smola, Hon...
AAAI
2011
12 years 8 months ago
Fast Newton-CG Method for Batch Learning of Conditional Random Fields
We propose a fast batch learning method for linearchain Conditional Random Fields (CRFs) based on Newton-CG methods. Newton-CG methods are a variant of Newton method for high-dime...
Yuta Tsuboi, Yuya Unno, Hisashi Kashima, Naoaki Ok...
WEBNET
2000
13 years 9 months ago
Using Multi-user Distributed Virtual Environments in Education
: On-line learning is one of the emerging needs of the information age. Access to education is going to become crucial for the success of our information society. Therefore a lot o...
Christos Bouras, Alexandros Philopoulos, Thrasyvou...
TIP
1998
129views more  TIP 1998»
13 years 8 months ago
Minimax partial distortion competitive learning for optimal codebook design
— The design of the optimal codebook for a given codebook size and input source is a challenging puzzle that remains to be solved. The key problem in optimal codebook design is h...
Ce Zhu, Lai-Man Po
ICASSP
2010
IEEE
13 years 6 months ago
Speech enhancement with sparse coding in learned dictionaries
The enhancement of speech degraded by non-stationary interferers is a highly relevant and difficult task of many signal processing applications. We present a monaural speech enhan...
Christian D. Sigg, Tomas Dikk, Joachim M. Buhmann