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» Experimental Evaluation of Hierarchical Hidden Markov Models
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KDD
2004
ACM
132views Data Mining» more  KDD 2004»
16 years 2 months ago
A probabilistic framework for semi-supervised clustering
Unsupervised clustering can be significantly improved using supervision in the form of pairwise constraints, i.e., pairs of instances labeled as belonging to same or different clu...
Sugato Basu, Mikhail Bilenko, Raymond J. Mooney
PERCOM
2006
ACM
15 years 8 months ago
Groupanizer: a Method to Correlate Multi-users Position with Daily Moments
Groupanizer is an extension of groupware and constitutes a development platform to integrate user-centric information for the benefit of groupware applications. User-centric conte...
Jean Olivier Caron, Yoshihiro Kawahara, Hiroyuki M...
TASLP
2002
84views more  TASLP 2002»
15 years 1 months ago
Substate tying with combined parameter training and reduction in tied-mixture HMM design
Two approaches are proposed for the design of tied-mixture hidden Markov models (TMHMM). One approach improves parameter sharing via partial tying of TMHMM states. To facilitate ty...
Liang Gu, Kenneth Rose
SECON
2010
IEEE
14 years 11 months ago
Deconstructing Interference Relations in WiFi Networks
Abstract--Wireless interference is the major cause of degradation of capacity in 802.11 wireless networks. We present an approach to estimate the interference between nodes and lin...
Anand Kashyap, Utpal Paul, Samir R. Das
92
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ICASSP
2011
IEEE
14 years 5 months ago
A supervised approach to movie emotion tracking
In this paper, we present experiments on continuous time, continuous scale affective movie content recognition (emotion tracking). A major obstacle for emotion research has been t...
Nikos Malandrakis, Alexandros Potamianos, Georgios...