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» Learning nonsingular phylogenies and hidden Markov models
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INTERSPEECH
2010
13 years 3 months ago
Incremental word learning using large-margin discriminative training and variance floor estimation
We investigate incremental word learning in a Hidden Markov Model (HMM) framework suitable for human-robot interaction. In interactive learning, the tutoring time is a crucial fac...
Irene Ayllón Clemente, Martin Heckmann, Ale...
FGR
2011
IEEE
209views Biometrics» more  FGR 2011»
13 years 7 days ago
Modeling hidden dynamics of multimodal cues for spontaneous agreement and disagreement recognition
— This paper attempts to recognize spontaneous agreement and disagreement based only on nonverbal multimodal cues. Related work has mainly used verbal and prosodic cues. We demon...
Konstantinos Bousmalis, Louis-Philippe Morency, Ma...
ICML
2004
IEEE
14 years 9 months ago
Learning low dimensional predictive representations
Predictive state representations (PSRs) have recently been proposed as an alternative to partially observable Markov decision processes (POMDPs) for representing the state of a dy...
Matthew Rosencrantz, Geoffrey J. Gordon, Sebastian...
ICML
2005
IEEE
14 years 9 months ago
Exploiting syntactic, semantic and lexical regularities in language modeling via directed Markov random fields
We present a directed Markov random field (MRF) model that combines n-gram models, probabilistic context free grammars (PCFGs) and probabilistic latent semantic analysis (PLSA) fo...
Shaojun Wang, Shaomin Wang, Russell Greiner, Dale ...
ICML
2000
IEEE
14 years 9 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...