Print edition: ISSN 0913-5685 Online edition: ISSN 2432-6380
[TOP] | [2013] | [2014] | [2015] | [2016] | [2017] | [2018] | [2019] | [Japanese] / [English]
IBISML2016-100
Tighter generalization bounds for matrix completion based on non-negative matrix factorization with norm constraints
Ken-ichiro Moridomi, Kohei Hatano, Eiji Takimoto (Kyushu Univ.)
pp. 1 - 8
IBISML2016-101
Exact calculation of grid-structured Markov random field model by corner transfer matrix method
Tomoharu Yoshida, Kazuho Watanabe, Kyoji Umemura (Toyohashi Univ. of Tech.)
pp. 9 - 16
IBISML2016-102
Degrees of freedom in submodular regularization
Kentaro Minami, Fumiyasu Komaki (The University of Tokyo)
pp. 17 - 24
IBISML2016-103
New Lerning Algorythm of Neural Network using Integral Representation and Kernel Herding
Takuo Matsubara, Sho Sonoda, Noboru Murata (Waseda Univ.)
pp. 25 - 31
IBISML2016-104
Recurrent Neural Networks for task-evoked fMRI data classification
Koya Ohashi (Tokyo Tech), Taiji Suzuki (Tokyo Tech/JST/RIKEN)
pp. 33 - 40
IBISML2016-105
Safe Pruning Rule for Predictive Sequential Pattern Mining and Its Application to Bio-logging Data Analysis
Kaoru Kishimoto (NITech), Masayuki Karasuyama (NIT), Kazuya Nakagawa (NITech), Kotaro Kimura (Osaka Univ.), Ken Yoda (Nagoya Univ.), Yuta Umezu, Shinsuke Kajioka (NITech), Koji Tsuda (UTokyo), Ichiro Takeuchi (NITech)
pp. 41 - 48
IBISML2016-106
Doubly Accelerated Stochastic Variance Reduced Gradient Method for Regularized Empirical Risk Minimization
Tomoya Murata, Taiji Suzuki (Tokyo Tech)
pp. 49 - 56
IBISML2016-107
A study on minimizing size of sparse model optimization problem: exploiting safe rules for keeping and removing variables
Masayuki Karasuyama (NIT/NIMS/JST), Atsushi Shibagaki (NIT), Ichiro Takeuchi (NIT/NIMS/RIKEN/NIMS)
pp. 57 - 62
IBISML2016-108
A stochastic optimization method and generalization bounds for voting classifiers by continuous density functions
Atsushi Nitanda (Tokyo Tech./NTTDATA MSI), Taiji Suzuki (Tokyo Tech./JST/RIKEN)
pp. 63 - 69
IBISML2016-109
Classification of In-week and -day Patterns of Ambulatory Activity Using a Hierarchical Topic Model and Interpolation of Step Counts in Missing Days
Shunichi Nomura (Tokyo Tech.), Michiko Watanabe, Yuko Oguma (Keio Univ.)
pp. 71 - 76
IBISML2016-110
Topic model for analysis of gene expression data
Koji Iwayama (Ryukoku Univ.), Atsushi J. Nagano (Ryukoku Univ./Kyoto Univ.)
pp. 77 - 82
IBISML2016-111
CTC network with explicit representation vector of Markov property
Yuta Kawachi, Taichi Asami, Yoshikazu Yamaguchi, Yushi Aono (NTT)
pp. 83 - 88
Note: Each article is a technical report without peer review, and its polished version will be published elsewhere.