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JMLR
2006
143views more  JMLR 2006»
14 years 9 months ago
Segmental Hidden Markov Models with Random Effects for Waveform Modeling
This paper proposes a general probabilistic framework for shape-based modeling and classification of waveform data. A segmental hidden Markov model (HMM) is used to characterize w...
Seyoung Kim, Padhraic Smyth
EWC
2011
84views more  EWC 2011»
14 years 4 months ago
A theoretical framework for an intelligent design catalogue
This paper outlines continuing work on the intelligent design catalogue. The intelligent design catalogue seeks to create a virtual design environment that is linked to a catalogu...
Paul Winkelman
73
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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
NIPS
2004
14 years 11 months ago
Support Vector Classification with Input Data Uncertainty
This paper investigates a new learning model in which the input data is corrupted with noise. We present a general statistical framework to tackle this problem. Based on the stati...
Jinbo Bi, Tong Zhang
JMLR
2008
168views more  JMLR 2008»
14 years 9 months ago
Max-margin Classification of Data with Absent Features
We consider the problem of learning classifiers in structured domains, where some objects have a subset of features that are inherently absent due to complex relationships between...
Gal Chechik, Geremy Heitz, Gal Elidan, Pieter Abbe...