Takaki Makino

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We explore the use of Support Vector Machines (SVMs) for biomedical named entity recognition. To make the SVM training with the available largest corpus – the GENIA corpus – tractable, we propose to split the non-entity class into sub-classes, using part-of-speech information. In addition, we explore new features such as word cache and the states of an HMM(More)
This paper presents the LiLFeS system, an efficient feature-structure description language for HPSG. The core engine of LiLFeS is an Abstract Machine for Attribute-Value Logics, proposed by Carpenter and Qu. Basic design policies, the current status, and performance evaluation of the LiLFeS system are described. The paper discusses two implementations of(More)
According to theories of cultural neuroscience, Westerners and Easterners may have distinct styles of cognition (e.g., different allocation of attention). Previous research has shown that Westerners and Easterners tend to utilize analytical and holistic cognitive styles, respectively. On the other hand, little is known regarding the cultural differences in(More)
We propose a new neural network architecture, called Simple Recurrent Temporal-Difference Networks (SR-TDNs), that learns to predict future observations in partially observable environments. SR-TDNs incorporate the structure of simple recurrent neural networks (SRNs) into temporal-difference (TD) networks to use proto-predictive representation of states.(More)
We propose a Deep Belief Net model for robust motion generation, which consists of two layers of Restricted Boltzmann Machines (RBMs). The lower layer has multiple RBMs for encoding real-valued spatial patterns of motion frames into compact representations. The upper layer has one conditional RBM for learning temporal constraints on transitions between(More)
We propose a computational theory on estimating the internal states of others, which is the basis of information processing in human communication. To estimate internal states of peers, we have to deal with two considerable difficulties, restricted dimension of estimator parameters and conversion of objective information into subjective. To solve these(More)
BACKGROUND This study investigated the relationships between psychopathy and impulsive and risky decision making, by utilizing intertemporal and probabilistic choices for both gain and loss, in addition to the Iowa gambling task. METHODS The Psychopathic Personality Inventory-Revised - a 154-item measure that assesses psychopathic traits by self-report -(More)