Print edition: ISSN 0913-5685 Online edition: ISSN 2432-6380
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IBISML2012-1
A study on an optimization algorithm for semi-supervised SVM using parametric programing
Kohei Ogawa, Ichiro Takeuchi (NIT), Masashi Sugiyama (Tokyo Tech)
pp. 1 - 8
IBISML2012-2
Learning Non-Linear Classifiers with a Sparsity Upper-Bound via Efficient Model Selection
Mathieu Blondel, Kazuhiro Seki, Kuniaki Uehara (Kobe Univ.)
pp. 9 - 14
IBISML2012-3
Online Prediction under Submodular Constraints
Daiki Suehiro, Kohei Hatano, Shuji Kijima, Eiji Takimoto (Kyushu Univ.), Kiyohito Nagano (Tokyo Univ.)
pp. 15 - 22
IBISML2012-4
Improving the Variable Setting of Softmax Selection From an Information-Theoretic Viewpoint
Kazunori Iwata (Hiroshima City Univ.)
pp. 23 - 30
IBISML2012-5
Detection of Earthquake-Induced Damage in Steel Structures By Applying Classification Algorithms to Changes in Vibration Characteristics
Mayako Yamaguchi, Masahiro Kurata (Kyoto Univ.)
pp. 31 - 34
IBISML2012-6
Topic Extraction Method by Semi-Supervised Latent Dirichlet Allocation for Real-Time Recommendation
Yasuhiro Ikeda, Ryoichi Kawahara, Hiroshi Saito (NTT)
pp. 35 - 40
IBISML2012-7
Locality-Sensitive Hashing With Margin Based Feature Selection
Makiko Konoshima (FJLAB)
pp. 41 - 47
IBISML2012-8
Density Difference Estimation
Masashi Sugiyama (Tokyo Inst. of Tech.), Takafumi Kanamori (Nagoya Univ.), Taiji Suzuki (Univ. of Tokyo), Marthinus Christoffel du Plessis, Song Liu (Tokyo Inst. of Tech.), Ichiro Takeuchi (Nagoya Inst. of Tech.)
pp. 49 - 56
IBISML2012-9
An MDL-based Change-Detection Algorithm for Piecewise Stationay Memoryless Sources with Multi-dimensional Parameter
Hiroki Kanazawa, Kenji Yamanishi (Univ. of Tokyo)
pp. 57 - 64
IBISML2012-10
On a Non-asymptotic Analysis Using Large Deviation Principles in the Multiarmed Bandit Problem
Junya Honda, Akimichi Takemura (Univ. of Tokyo)
pp. 65 - 72
IBISML2012-11
Accuracy of the Bayes Latent Variable Estimation from Mixture of Complete and Incomplete Data
Keisuke Yamazaki (Tokyo Tech)
pp. 73 - 77
IBISML2012-12
Winning the Kaggle Algorithmic Trading Challenge with the Composition of Many Models and Feature Engineering
Ildefons Magrans de Abril, Masashi Sugiyama (Tokyo Inst. of Tech.)
pp. 79 - 84
Note: Each article is a technical report without peer review, and its polished version will be published elsewhere.