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CORR
2010
Springer
122views Education» more  CORR 2010»
14 years 8 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»
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
ICML
2008
IEEE
16 years 2 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
16 years 3 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
16 years 2 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...