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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 7 of 7  /   
Committee Date Time Place Paper Title / Authors Abstract Paper #
IBISML 2018-03-05
14:15
Fukuoka Nishijin Plaza, Kyushu University Exponential Family of Markov Kernels and Asymptotic Exponential Family of Markov Sources
Jun'ichi Takeuchi (Kyushu Univ.), Hiroshi Nagaoka (UEC) IBISML2017-93
For parametric models of Markov sources, we prove that the notion of asymptotic exponential family is equivalent to the ... [more] IBISML2017-93
pp.21-25
IT 2017-07-14
15:10
Chiba Chiba University On Information Geometry of Tree Models
Jun'ichi Takeuchi (Kyushu Univ.), Hiroshi Nagaoka (UEC) IT2017-35
We discuss information geometrical properties of the familes of Markov sources defined based on context trees. [more] IT2017-35
pp.109-113
IT 2017-07-14
15:35
Chiba Chiba University Asymptotic Exponential Family of Markov Sources is Equivalent to Exponential Family of Markov Kernels
Jun'ichi Takeuchi (Kyushu Univ.), Hiroshi Nagaoka (UEC) IT2017-36
For familes of Markov models, we prove that the notion of asymptotic exponential familly is equivalent to the notion of ... [more] IT2017-36
pp.115-119
NC, IPSJ-BIO, IBISML, IPSJ-MPS [detail] 2017-06-25
09:30
Okinawa Okinawa Institute of Science and Technology Expectation Propagation for t-Exponential Family
Futoshi Futami, Issei Sato (Univ. of Tokyo/RIKEN), Masashi Sugiyama (RIKEN/Univ. of Tokyo) IBISML2017-6
Exponential family distributions are highly useful in machine learning since their calculation can be performed efficien... [more] IBISML2017-6
pp.179-184
PRMU, IBISML, IPSJ-CVIM [detail] 2015-09-14
13:00
Ehime   On the statistical properties and parametrization of curved exponential families -- from the view point of $tau$-information geometry --
Masaru Tanaka (Fukuoka Univ.) PRMU2015-69 IBISML2015-29
For curved exponential family, its statistical properties depend on a parameterization. In 1982, Hougaard gives single d... [more] PRMU2015-69 IBISML2015-29
pp.13-18
R 2013-12-13
14:35
Tokyo   A Comparative Study of NHPP-based Software Reliability Models with Exponentiated Distributions
Xiao Xiao (Tokyo Metropolitan Univ.), Tadashi Dohi (Hiroshima Univ.) R2013-82
The non-homogeneous Poisson processes (NHPPs) based software reliability models (SRMs) have gained much popularity in ac... [more] R2013-82
pp.19-24
NC 2006-03-15
09:55
Tokyo Tamagawa University Parameter dimension reduction method for mixture models based on information geometry
Shotaro Akaho (AIST)
Dimension reduction for a set of distribution parameters
has been quite important in various kinds of applications.
... [more]
NC2005-115
pp.57-62
 Results 1 - 7 of 7  /   
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