Search Results - "Torisawa, Kentaro"

Automatic Graph Partitioning for Very Large-scale Deep Learning by Tanaka, Masahiro, Taura, Kenjiro, Hanawa, Toshihiro, Torisawa, Kentaro

“…This work proposes RaNNC (Rapid Neural Network Connector) as middleware for automatic hybrid parallelism. In recent deep learning research, as exemplified by…”
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Low Latency and Resource-Aware Program Composition for Large-Scale Data Analysis by Tanaka, Masahiro, Taura, Kenjiro, Torisawa, Kentaro

“…The importance of large-scale data analysis has shown a recent increase in a wide variety of areas, such as natural language processing, sensor data analysis,…”
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Effectiveness of Moldable and Malleable Scheduling in Deep Learning Tasks by Fujiwara, Ikki, Tanaka, Masahiro, Taura, Keniiro, Torisawa, Kentaro

“…Research and development of deep learning (DL) applications often involves exhaustive trial-and-error, which demands that shared computational resources,…”
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EXPLOITING SUBTREES IN AUTO-PARSED DATA TO IMPROVE DEPENDENCY PARSING by Chen, Wenliang, Kazama, Jun'ichi, Uchimoto, Kiyotaka, Torisawa, Kentaro

“…Dependency parsing has attracted considerable interest from researchers and developers in natural language processing. However, to obtain a high‐accuracy…”
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Analysis of the degree of importance of information using newspapers and questionnaires by Murata, M., Kanamaru, T., Nishimura, R., Torisawa, K., Doi, K.

“…Our objective is to estimate and clarify the factors that determine the degree of importance of information by extracting the words that characterize the…”
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Bitext Dependency Parsing With Auto-Generated Bilingual Treebank by Wenliang Chen, Kazama, J., Min Zhang, Tsuruoka, Y., Yujie Zhang, Yiou Wang, Torisawa, K., Haizhou Li

“…This paper proposes a method to improve the accuracy of bilingual texts (bitexts) dependency parsing by using an auto-generated bilingual treebank created with…”
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Using the Maximum Entropy Method for Natural Language Processing: Category Estimation, Feature Extraction, and Error Correction by Murata, Masaki, Uchimoto, Kiyotaka, Utiyama, Masao, Ma, Qing, Nishimura, Ryo, Watanabe, Yasuhiko, Doi, Kouichi, Torisawa, Kentaro

“…The maximum entropy (ME) method is a powerful supervised machine learning technique that is useful for various tasks. In this paper, we introduce new studies…”
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Automatic Graph Partitioning for Very Large-scale Deep Learning by Tanaka, Masahiro, Taura, Kenjiro, Hanawa, Toshihiro, Torisawa, Kentaro

“…This work proposes RaNNC (Rapid Neural Network Connector) as middleware for automatic hybrid parallelism. In recent deep learning research, as exemplified by…”
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Organizing the Web's Information Explosion to Discover Unknown Unknowns by Torisawa, Kentaro, De Saeger, Stijn, Kazama, Jun’ichi, Sumida, Asuka, Noguchi, Daisuke, Kakizawa, Yasunori, Murata, Masaki, Kuroda, Kow, Yamada, Ichiro

“…This paper introduces the TORISHIKI-KAI project, which aims to construct a million-word-scale semantic network from the Web using state of the art knowledge…”
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Autonomic Resource Management for Program Orchestration in Large-Scale Data Analysis by Tanaka, Masahiro, Taura, Kenjiro, Torisawa, Kentaro

“…Large-scale data analysis applications are becoming more and more prevalent in a wide variety of areas. These applications are composed of many currently…”
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Large Scale Relation Acquisition Using Class Dependent Patterns by De Saeger, S., Torisawa, K., Kazama, J., Kuroda, K., Murata, M.

“…This paper proposes a minimally supervised method for acquiring high-level semantic relations such as causality and prevention from the Web. Our method learns…”
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A Novel Web-Oriented Writing Environment Using Objects' Facts Acquired from the Web by Yoshinaga, Naoki, Nakamura, Kazumasa, Torisawa, Kentaro

“…This paper presents a novel web-oriented writing environment that helps users describe their opinions on topics/events through weblogs, by showing facts…”
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Large scale similarity-based relation expansion by Tsuchidal, Masaaki, De Saeger, Stijn, Torisawa, Kentaro, Murata, Masaki, Kazama, Jun'ichi, Kuroda, Kow, Ohwada, Hayato

“…Recent advances in automatic knowledge acquisition methods make it possible to construct massive knowledge bases of semantic relations, containing information…”
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The NICT concept dictionary by Stijin, De Saeger, Kentaro, Torisawa, Jun'ichi, Kazama, Kiyonori, Ohtake, Isrvan, Varga, Yulan, Yan

“…Summary form only given. In this demonstration we present a system that guides a user's information search (or knowledge discovery) by displaying, in a…”
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TORISHIKI-KAI, An Autogenerated Web Search Directory by Torisawa, Kentaro, De Saeger, Stijn, Kakizawa, Yasunori, Kazama, Jun'ichi, Murata, Masaki, Noguchi, Daisuke, Sumida, Asuka

“…With this research we present a system that suggests valuable complementary information relevant to a user's topic of interest, in the form of keywords. For…”
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Enriching Multilingual Language Resources by Discovering Missing Cross-Language Links in Wikipedia by Oh, Jong-Hoon, Kawahara, Daisuke, Uchimoto, Kiyotaka, Kazama, Jun'ichi, Torisawa, Kentaro

“…We present a novel method for discovering missing cross-language links between English and Japanese Wikipedia articles. We collect candidates of missing…”
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Generating information-rich taxonomy from Wikipedia by Yamada, I, Hashimoto, C, Jong-Hoon Oh, Torisawa, K, Kuroda, K, De Saeger, S, Tsuchida, M, Kazama, J

“…Even though hyponymy relation acquisition has been extensively studied, "how informative such acquired hyponymy relations are" has not been sufficiently…”
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A Novel Web-Oriented Writing Environment Using Objects' Facts Acquired from the Web by Yoshinaga, N., Nakamura, K., Torisawa, K.

“…This paper presents a novel web-oriented writing environment that helps users describe their opinions on topics/events through weblogs, by showing facts…”
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Extraction and visualization of numerical and named entity information from a large number of documents by Murata, M., Qing Ma, Torisawa, K., Iwatate, M., Shirado, T., Ichii, K., Kanamaru, T.

“…We have developed a system that can semi automatically extract numerical and named entity sets from a large number of Japanese documents and can create various…”
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