TY - GEN
T1 - Modeling group dynamics using graphical models and tensor decompositions
AU - Li, Lin
AU - Swami, Ananthram
AU - Scaglione, Anna
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2014/2/5
Y1 - 2014/2/5
N2 - We propose a general modeling framework for learning group dynamics in data collected from multiple information sources and over time. In particular, groups are characterized by specific temporal patterns based on hidden Markov models. Tensor decomposition techniques combined with graphical models are used to extract group information from the observed data.
AB - We propose a general modeling framework for learning group dynamics in data collected from multiple information sources and over time. In particular, groups are characterized by specific temporal patterns based on hidden Markov models. Tensor decomposition techniques combined with graphical models are used to extract group information from the observed data.
UR - http://www.scopus.com/inward/record.url?scp=84983152448&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84983152448&partnerID=8YFLogxK
U2 - 10.1109/GlobalSIP.2014.7032228
DO - 10.1109/GlobalSIP.2014.7032228
M3 - Conference contribution
AN - SCOPUS:84983152448
T3 - 2014 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2014
SP - 793
EP - 797
BT - 2014 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2014
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2014 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2014
Y2 - 3 December 2014 through 5 December 2014
ER -