4.3k citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- The University of TokyoJP154 papers
- National Astronomical Observatory of JapanJP111 papers
- The Graduate University for Advanced Studies, SOKENDAIJP101 papers
- Kavli Institute for the Physics and Mathematics of the UniverseJP67 papers
- Nagoya UniversityJP57 papers
- Hiroshima UniversityJP47 papers
- Centre National de la Recherche ScientifiqueFR45 papers
- Tohoku UniversityJP42 papers
- University College LondonGB42 papers
- Institute of Astronomy and Astrophysics, Academia SinicaTW41 papers
- Korea Astronomy and Space Science InstituteKR41 papers
- Tokyo Institute of TechnologyJP41 papers
24 papers · 1 filter
Data Compression for the Tomo-e Gozen with Low-rank Matrix Approximation
Mikio Morii, Shiro Ikeda, Shigeyuki Sako +1
Optical wide-field surveys with a high cadence are expected to create a new field of astronomy, so-called "movie astronomy," in the near future. The amount of data of the observati…
A simple method to construct confidence bands in functional linear regression
Masaaki Imaizumi, Kengo Kato
This paper develops a simple method to construct confidence bands, centered at a principal component analysis (PCA) based estimator, for the slope function in a functional linear r…
Accelerating cross-validation with total variation and its application to super-resolution imaging
Tomoyuki Obuchi, Shiro Ikeda, Kazunori Akiyama +1
We develop an approximation formula for the cross-validation error (CVE) of a sparse linear regression penalized by -norm and total variation terms, which is based on a per…
Sparse principal component regression for generalized linear models
Shuichi Kawano, Hironori Fujisawa, Toyoyuki Takada +1
Principal component regression (PCR) is a widely used two-stage procedure: principal component analysis (PCA), followed by regression in which the selected principal components are…
Machine-learning Selection of Optical Transients in Subaru/Hyper Suprime-Cam Survey
Mikio Morii, Shiro Ikeda, Nozomu Tominaga +8
We present an application of machine-learning (ML) techniques to source selection in the optical transient survey data with Hyper Suprime-Cam (HSC) on the Subaru telescope. Our goa…
Robustness analysis of bimodal networks in the whole range of degree correlation
Shogo Mizutaka, Toshihiro Tanizawa
We present exact analysis of the physical properties of bimodal networks specified by the two peak degree distribution fully incorporating the degree-degree correlation between nod…
Non-area-specific adjustment factor for second-order efficient empirical Bayes confidence interval
Masayo Y. Hirose
An empirical Bayes confidence interval has high user demand in many applications. In particular, the second-order empirical Bayes confidence interval, the coverage error of which i…
Partition structure and the A-hypergeometric distribution associated with the rational normal curve
Shuhei Mano
A distribution whose normalization constant is an A-hypergeometric polynomial is called an A-hypergeometric distribution. Such a distribution is in turn a generalization of the gen…
The forecasting of menstruation based on a state-space modeling of basal body temperature time series
Keiichi Fukaya, Ai Kawamori, Yutaka Osada +2
Women's basal body temperature (BBT) follows a periodic pattern that is associated with the events in their menstrual cycle. Although daily BBT time series contain potentially usef…
The Bivariate Lack-of-Memory Distributions
Gwo Dong Lin, Xiaoling Dou, Satoshi Kuriki
We treat all the bivariate lack-of-memory (BLM) distributions in a unified approach and develop some new general properties of the BLM distributions, including joint moment generat…
Numerical validation of blow-up solutions of ordinary differential equations
Akitoshi Takayasu, Kaname Matsue, Takiko Sasaki +3
This paper focuses on blow-up solutions of ordinary differential equations (ODEs). We present a method for validating blow-up solutions and their blow-up times, which is based on c…
A multistate dynamic site occupancy model for spatially aggregated sessile communities
Keiichi Fukaya, J. Andrew Royle, Takehiro Okuda +2
Markov community models have been applied to sessile organisms because such models facilitate estimation of transition probabilities by tracking species occupancy at many fixed obs…
Kernel Mean Embedding of Distributions: A Review and Beyond
Krikamol Muandet, Kenji Fukumizu, Bharath Sriperumbudur +1
A Hilbert space embedding of a distribution---in short, a kernel mean embedding---has recently emerged as a powerful tool for machine learning and inference. The basic idea behind…
Convergence guarantees for kernel-based quadrature rules in misspecified settings
Motonobu Kanagawa, Bharath K. Sriperumbudur, Kenji Fukumizu
Kernel-based quadrature rules are becoming important in machine learning and statistics, as they achieve super- convergence rates in numerical integration, and thus provi…
On the construction of Lyapunov functions with computer assistance
Kaname Matsue, Tomohiro Hiwaki, Nobito Yamamoto
Computer assisted procedures of Lyapunov functions defined in given neighborhoods of fixed points for flows and maps are discussed. We provide a systematic methodology for construc…
PRECL: A new method for interferometry imaging from closure phase
Shiro Ikeda, Fumie Tazaki, Kazunori Akiyama +2
For short-wavelength VLBI observations, it is difficult to measure the phase of the visibility function accurately. The closure phases are reliable measurements under this situatio…
A note on the spectral mapping theorem of quantum walk models
Kaname Matsue, Osamu Ogurisu, Etsuo Segawa
We discuss the description of eigenspace of a quantum walk model with an associating linear operator in abstract settings of quantum walk including the Szegedy walk on grap…
Robust and Sparse Regression via -divergence
Takayuki Kawashima, Hironori Fujisawa
In high-dimensional data, many sparse regression methods have been proposed. However, they may not be robust against outliers. Recently, the use of density power weight has been st…
Statistical properties of fluctuations of time series representing the appearance of words in nationwide blog data and their applications: An example of observations and the modelling of fluctuation scalings of nonstationary time series
Hayafumi Watanabe, Yukie Sano, Hideki Takayasu +1
To elucidate the non-trivial empirical statistical properties of fluctuations of a typical non-steady time series representing the appearance of words in blogs, we investigated app…
Evaluation of Generalized Degrees of Freedom for Sparse Estimation by Replica Method
Ayaka Sakata
We develop a method to evaluate the generalized degrees of freedom (GDF), which is a key quantity of a model selection criterion, for linear regression with sparse regularization.…
Application of the Ghosh & Lamb Relation to the Spin-up/down Behavior in the X-ray Binary Pulsar 4U 1626-67
Toshihiro Takagi, Tatehiro Mihara, Mutsumi Sugizaki +2
We analyzed continuous MAXI/GSC data of the X-ray binary pulsar 4U 1626-67 from 2009 October to 2013 September, and determined the pulse period and the pulse-period derivative for…
Search for Soft X-ray Flashes at Fireball Phase of Classical/Recurrent Novae using MAXI/GSC data
Mikio Morii, Hitoshi Yamaoka, Tatehiro Mihara +2
We searched for precursive soft X-ray flashes (SXFs) associated with optically-discovered classical or recurrent novae in the data of five-years all-sky observations with Gas Slit…
Equivalence between direct and indirect effects with different sets of intermediate variables and covariates
Manabu Kuroki
This paper deals with the concept of equivalence between direct and indirect effects of a treatment on a response using two sets of intermediate variables and covariates. First, we…
Persistence weighted Gaussian kernel for topological data analysis
Genki Kusano, Kenji Fukumizu, Yasuaki Hiraoka
Topological data analysis (TDA) is an emerging mathematical concept for characterizing shapes in complex data. In TDA, persistence diagrams are widely recognized as a useful descri…