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» Learning nonsingular phylogenies and hidden Markov models
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INTERSPEECH
2010
15 years 1 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»
14 years 10 months 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
16 years 7 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
16 years 7 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
16 years 7 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...