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CVPR
1999
IEEE
14 years 9 months ago
Time-Series Classification Using Mixed-State Dynamic Bayesian Networks
We present a novel mixed-state dynamic Bayesian network (DBN) framework for modeling and classifying timeseries data such as object trajectories. A hidden Markov model (HMM) of di...
Vladimir Pavlovic, Brendan J. Frey, Thomas S. Huan...
ICMCS
2005
IEEE
173views Multimedia» more  ICMCS 2005»
14 years 1 months ago
A Multi-Modal Mixed-State Dynamic Bayesian Network for Robust Meeting Event Recognition from Disturbed Data
In this work we present a novel multi-modal mixed-state dynamic Bayesian network (DBN) for robust meeting event classification. The model uses information from lapel microphones,...
Marc Al-Hames, Gerhard Rigoll
IEEEICCI
2003
IEEE
14 years 1 months ago
Mixing Semantic Networks and Conceptual Vectors: The Case of Hyperonymy
In this paper, we focus on lexical semantics, a key issue in Natural Language Processing (NLP) that tends to converge with conceptual Knowledge Representation (KR) and ontologies....
Violaine Prince, Mathieu Lafourcade
UAI
1998
13 years 9 months ago
A Multivariate Discretization Method for Learning Bayesian Networks from Mixed Data
In this paper we address the problem of discretization in the context of learning Bayesian networks (BNs) from data containing both continuous and discrete variables. We describe ...
Stefano Monti, Gregory F. Cooper
GLOBECOM
2010
IEEE
13 years 5 months ago
Mixed Time-Scale Generalized Fair Scheduling for Amplify-and-Forward Relay Networks
Abstract--We devise an optimization framework for generalized proportional fairness (GPF) under different time scales for amplify-and-forward (AF) relay networks. In GPF scheduling...
Alireza Sharifian, Petar Djukic, Halim Yanikomerog...