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CORR
2010
Springer
122views Education» more  CORR 2010»
14 years 4 months ago
Concavity of Mutual Information Rate for Input-Restricted Finite-State Memoryless Channels at High SNR
We consider a finite-state memoryless channel with i.i.d. channel state and the input Markov process supported on a mixing finite-type constraint. We discuss the asymptotic behavio...
Guangyue Han, Brian H. Marcus
TASLP
2002
84views more  TASLP 2002»
14 years 9 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
ICML
2008
IEEE
15 years 10 months ago
A distance model for rhythms
Modeling long-term dependencies in time series has proved very difficult to achieve with traditional machine learning methods. This problem occurs when considering music data. In ...
Douglas Eck, Jean-François Paiement, Samy B...
ICIP
2004
IEEE
15 years 11 months ago
Action modeling with volumetric data
In this paper we propose and test an action recognition algorithm in which the images of the scene captured by a significant number of cameras are first used to generate a volumet...
Fabio Cuzzolin, Augusto Sarti, Stefano Tubaro
ICML
2000
IEEE
15 years 10 months ago
Maximum Entropy Markov Models for Information Extraction and Segmentation
Hidden Markov models (HMMs) are a powerful probabilistic tool for modeling sequential data, and have been applied with success to many text-related tasks, such as part-of-speech t...
Andrew McCallum, Dayne Freitag, Fernando C. N. Per...