Tokyo Institute of Technology

About: Tokyo Institute of Technology is a education organization based out in Tokyo, Tôkyô, Japan. It is known for research contribution in the topics: Catalysis & Thin film. The organization has 46775 authors who have published 101656 publications receiving 2357893 citations. The organization is also known as: Tokyo Tech & Tokodai.

Weak Convergence Theorem by an Extragradient Method for Nonexpansive Mappings and Monotone Mappings

Abstract: In this paper, we introduce an iterative process for finding the common element of the set of fixed points of a nonexpansive mapping and the set of solutions of the variational inequality problem for a monotone, Lipschitz-continuous mapping. The iterative process is based on the so-called extragradient method. We obtain a weak convergence theorem for two sequences generated by this process

Patrolling monocytes control tumor metastasis to the lung

Abstract: The immune system plays an important role in regulating tumor growth and metastasis. Classical monocytes promote tumorigenesis and cancer metastasis, but how nonclassical "patrolling" monocytes (PMo) interact with tumors is unknown. Here we show that PMo are enriched in the microvasculature of the lung and reduce tumor metastasis to lung in multiple mouse metastatic tumor models. Nr4a1-deficient mice, which specifically lack PMo, showed increased lung metastasis in vivo. Transfer of Nr4a1-proficient PMo into Nr4a1-deficient mice prevented tumor invasion in the lung. PMo established early interactions with metastasizing tumor cells, scavenged tumor material from the lung vasculature, and promoted natural killer cell recruitment and activation. Thus, PMo contribute to cancer immunosurveillance and may be targets for cancer immunotherapy.

Asymptotic Equivalence of Bayes Cross Validation and Widely Applicable Information Criterion in Singular Learning Theory

Abstract: In regular statistical models, the leave-one-out cross-validation is asymptotically equivalent to the Akaike information criterion. However, since many learning machines are singular statistical models, the asymptotic behavior of the cross-validation remains unknown. In previous studies, we established the singular learning theory and proposed a widely applicable information criterion, the expectation value of which is asymptotically equal to the average Bayes generalization loss. In the present paper, we theoretically compare the Bayes cross-validation loss and the widely applicable information criterion and prove two theorems. First, the Bayes cross-validation loss is asymptotically equivalent to the widely applicable information criterion as a random variable. Therefore, model selection and hyperparameter optimization using these two values are asymptotically equivalent. Second, the sum of the Bayes generalization error and the Bayes cross-validation error is asymptotically equal to $2\lambda/n$, where $\lambda$ is the real log canonical threshold and $n$ is the number of training samples. Therefore the relation between the cross-validation error and the generalization error is determined by the algebraic geometrical structure of a learning machine. We also clarify that the deviance information criteria are different from the Bayes cross-validation and the widely applicable information criterion.

Indications of intermediate-scale anisotropy of cosmic rays with energy greater than 57 EeV in the northern sky measured with the surface detector of the Telescope Array experiment

Abstract: We have searched for intermediate-scale anisotropy in the arrival directions of ultrahigh-energy cosmic rays with energies above 57 EeV in the northern sky using data collected over a 5 yr period by the surface detector of the Telescope Array experiment. We report on a cluster of events that we call the hotspot, found by oversampling using 20° radius circles. The hotspot has a Li-Ma statistical significance of 5.1σ, and is centered at R.A. = 146.°7, decl. = 43.°2. The position of the hotspot is about 19° off of the supergalactic plane. The probability of a cluster of events of 5.1σ significance, appearing by chance in an isotropic cosmic-ray sky, is estimated to be 3.7 × 10-4 (3.4σ). © 2014. The American Astronomical Society. All rights reserved.