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Technical Committee on Information-Based Induction Sciences and Machine Learning (IBISML) (Searched in: 2014)
Search Results: Keywords 'from:2014-11-17 to:2014-11-17'
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| IBISML | 2014-11-17 17:00 |
Aichi | Nagoya Univ. | [Poster Presentation]
Application of partial parallel interference cancellation to sparse signal recovery Koujin Takeda (Ibaraki Univ.), Toshiyuki Tanaka (Kyoto Univ.)  IBISML2014-35 |
We apply partial parallel interference cancellation scheme in CDMA demodulation to sparse signal recovery in compressed ... [more] | IBISML2014-35 pp.1-7 |
| IBISML | 2014-11-17 17:00 |
Aichi | Nagoya Univ. | [Poster Presentation]
Feature Extraction for Image Classification using Restricted Boltzmann Machines Reiki Suda, Koujin Takeda (Ibaraki Univ.) IBISML2014-36 |
Learning restricted Boltzmann machines (RBMs) for high-dimensional data using maximum likelihood estimation had been fac... [more] | IBISML2014-36 pp.9-15 |
| IBISML | 2014-11-17 17:00 |
Aichi | Nagoya Univ. | [Poster Presentation]
Approximate Models of Probability Distributions for Principal Components of Sample Mahalanobis Distances
-- About Each Element and Partial Sum of Sample Mahalanobis Distances -- Yasuyuki Kobayashi (Teikyo Univ.) IBISML2014-37 |
Probability distributions of the principal components and their partial sum, into which a sample Mahalanobis distance is... [more] | IBISML2014-37 pp.17-24 |
| IBISML | 2014-11-17 17:00 |
Aichi | Nagoya Univ. | [Poster Presentation]
Theoretical Analysis of Empirical MAP and Empirical Partially Bayes Shinichi Nakajima (TU Berlin), Masashi Sugiyama (Univ. of Tokyo) IBISML2014-38 |
Variational Bayesian (VB) learning is known to be a promising approximation to Bayesian learning with computational... [more] |
IBISML2014-38 pp.25-32 |
| IBISML | 2014-11-17 17:00 |
Aichi | Nagoya Univ. | [Poster Presentation]
Entropy Estimators Based on Simple Linear Regression Hideitsu Hino (Univ. of Tukuba), Kensuke Koshijima (Recruit), Noboru Murata (Waseda Univ.) IBISML2014-39 |
Three differential entropy estimators are proposed based on the second order expansion of the probability mass around th... [more] | IBISML2014-39 pp.33-40 |
| IBISML | 2014-11-17 17:00 |
Aichi | Nagoya Univ. | [Poster Presentation]
Importance-Weighted Covariance Estimation for Robust Common Spatial Pattern Alessandro Balzi (PoliMi), Florian Yger, Masashi Sugiyama (Univ. of Tokyo) IBISML2014-40 |
Non-stationarity is an important issue for practical applications of machine learning methods. This issue particularly a... [more] | IBISML2014-40 pp.41-48 |
| IBISML | 2014-11-17 17:00 |
Aichi | Nagoya Univ. | [Poster Presentation]
Breakdown Point of Robust Support Vector Machine Takafumi Kanamori (Nagoya Univ.), Shuhei Fujiwara, Akiko Takeda (Univ. of Tokyo) IBISML2014-41 |
The support vector machine (SVM) is one of the most successful learning methods for solving classification problems. D... [more] |
IBISML2014-41 pp.49-56 |
| IBISML | 2014-11-17 17:00 |
Aichi | Nagoya Univ. | [Poster Presentation]
Possibilities and limitations of machine learning on unweighted graphs
-- From the viewpoint of random geometric graph theory -- Yoshikazu Terada (NICT), Ulrike von Luxburg (Univ. of Hamburg) IBISML2014-42 |
We study the problem of ordinal embedding: given a set of ordinal constraints of the form $distance(i, j) < distance(k, ... [more] | IBISML2014-42 pp.57-64 |
| IBISML | 2014-11-17 17:00 |
Aichi | Nagoya Univ. | [Poster Presentation]
Exact SVM Training by Wolfe's Minimum Norm Point Algorithm Masashi Kitamura, Akiko Takeda, Satoru Iwata (Univ. of Tokyo) IBISML2014-43 |
(Advance abstract in Japanese is available) [more] | IBISML2014-43 pp.65-71 |
| IBISML | 2014-11-17 17:00 |
Aichi | Nagoya Univ. | [Poster Presentation]
Efficient leave-one-out cross-validation for L2-regularized classifier Shota Okumura, Yoshiki Suzuki, Kohei Ogawa, Yuki Shinmura, Ichiro Takeuchi (NIT) IBISML2014-44 |
Leave-one-out cross-validation (LOOCV) is a useful tool for estimating generalization performances of various machine ... [more] |
IBISML2014-44 pp.73-80 |
| IBISML | 2014-11-17 17:00 |
Aichi | Nagoya Univ. | [Poster Presentation]
Geometry of Fisher's linear discriminant analysis Jun Fujiki, Masaru Tanaka (Fukuoka Univ.), Hitoshi Sakano (NTT data), Akisato Kimura (NTT) IBISML2014-45 |
(Advance abstract in Japanese is available) [more] | IBISML2014-45 pp.81-86 |
| IBISML | 2014-11-17 17:00 |
Aichi | Nagoya Univ. | [Poster Presentation]
Heuristic principal component analysis based unsupervised feature extraction and its application to bioinformatics Y-h. Taguchi (Chuo Univ) IBISML2014-46 |
: Feature extraction (FE) is a difficult task when the number of features is much larger than the number of samples, a... [more] |
IBISML2014-46 pp.87-94 |
| IBISML | 2014-11-17 17:00 |
Aichi | Nagoya Univ. | [Poster Presentation]
Differential Privacy on Linear Regression Model of Crowdsensing Tran Quang Khai, Kazuto Fukuchi, Jun Sakuma (Univ. of Tsukuba) IBISML2014-47 |
Learning statistic models using the data collected from crowd is one of the important tasks in the crowdsensing. Crowdse... [more] | IBISML2014-47 pp.95-102 |
| IBISML | 2014-11-17 17:00 |
Aichi | Nagoya Univ. | [Poster Presentation]
Reconstructive Neural Net based on Context Free Grammar Takuo Hamaguchi, Masashi Shimbo, Yuji Matsumoto (NAIST) IBISML2014-48 |
There are two aspects about Neural Language Model,one aspect, `Encode', obtains a vector from a sequence and the other a... [more] | IBISML2014-48 pp.103-110 |
| IBISML | 2014-11-17 17:00 |
Aichi | Nagoya Univ. | [Poster Presentation]
Multitask learning meets tensor factorization: task imputation via convex optimization Kishan Wimalawarne (Tokyo Inst. of Tech.), Masashi Sugiyama (Univ. of Tokyo), Ryota Tomioka (TTIC) IBISML2014-49 |
We study a multitask learning problem in which each task is parametrized by a weight vector and indexed by a pair of ind... [more] | IBISML2014-49 pp.111-118 |
| IBISML | 2014-11-17 17:00 |
Aichi | Nagoya Univ. | [Poster Presentation]
Statistical mechanical analysis of lossy compression by overcomplete basis Yoshinori Nakanishi-Ohno (Univ. Tokyo), Tomoyuki Obuchi (Tokyo Tech), Masato Okada (Univ. Tokyo), Yoshiyuki Kabashima (Tokyo Tech) IBISML2014-50 |
Information processing using the sparsity of information has been actively studied such as compressed sensing. In this ... [more] |
IBISML2014-50 pp.119-126 |
| IBISML | 2014-11-17 17:00 |
Aichi | Nagoya Univ. | [Poster Presentation]
Direct Density Ratio Estimation with Convolutional Neural Networks with Application in Outlier Detection Hyunha Nam (Tokyo Inst. of Tech.), Masashi Sugiyama (Univ. of Tokyo) IBISML2014-51 |
(Advance abstract in Japanese is available) [more] | IBISML2014-51 pp.127-132 |
| IBISML | 2014-11-17 17:00 |
Aichi | Nagoya Univ. | [Poster Presentation]
Direct Density-Derivative Estimation and Its Application in KL-Divergence Approximation Hiroaki Sasaki (Univ. of Tokyo), Yung-Kyun Noh (KAIST), Masashi Sugiyama (Univ. of Tokyo) IBISML2014-52 |
Estimation of density derivatives is a versatile tool in statistical data analysis. A naive approach is to first estimat... [more] | IBISML2014-52 pp.133-140 |
| IBISML | 2014-11-17 17:00 |
Aichi | Nagoya Univ. | [Poster Presentation]
An Online Policy Gradient Algorithm for Continuous State and Action Markov Decision Processes with Bandit Feedback Yao Ma (Tokyo Inst. of Tech.), Masashi Sugiyama (Univ. of Tokyo) IBISML2014-53 |
[more] | IBISML2014-53 pp.141-148 |
| IBISML | 2014-11-17 17:00 |
Aichi | Nagoya Univ. | [Poster Presentation]
Efficient Method for Computing Belief Propagation, with Application to CDMA Multiuser Detection Arise Kuriya, Toshiyuki Tanaka (Kyoto Univ) IBISML2014-54 |
Pearl's belief propagation (BP) is an algorithm to solve inference problems on probability models defined in terms of ... [more] |
IBISML2014-54 pp.149-153 |
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