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» Learning a Continuous Hidden Variable Model for Binary Data
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NIPS
2004
13 years 9 months ago
Multiple Alignment of Continuous Time Series
Multiple realizations of continuous-valued time series from a stochastic process often contain systematic variations in rate and amplitude. To leverage the information contained i...
Jennifer Listgarten, Radford M. Neal, Sam T. Rowei...
ICIP
2004
IEEE
14 years 9 months ago
Automatically learning structural units in educational videos with the hierarchical hidden markov models
In this paper we present a coherent approach using the hierarchical HMM with shared structures to extract the structural units that form the building blocks of an education/traini...
Dinh Q. Phung, Svetha Venkatesh, Hung Hai Bui
JAIR
2008
164views more  JAIR 2008»
13 years 7 months ago
Gesture Salience as a Hidden Variable for Coreference Resolution and Keyframe Extraction
Gesture is a non-verbal modality that can contribute crucial information to the understanding of natural language. But not all gestures are informative, and non-communicative hand...
Jacob Eisenstein, Regina Barzilay, Randall Davis
ICML
2003
IEEE
14 years 8 months ago
Learning on the Test Data: Leveraging Unseen Features
This paper addresses the problem of classification in situations where the data distribution is not homogeneous: Data instances might come from different locations or times, and t...
Benjamin Taskar, Ming Fai Wong, Daphne Koller
ICML
2010
IEEE
13 years 8 months ago
Hilbert Space Embeddings of Hidden Markov Models
Hidden Markov Models (HMMs) are important tools for modeling sequence data. However, they are restricted to discrete latent states, and are largely restricted to Gaussian and disc...
Le Song, Sajid M. Siddiqi, Geoffrey J. Gordon, Ale...