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Photo Yoshinobu Kawahara
Osaka University, The Institute of Scientific and Industrial Research, Associate Professor
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Knowledge discovery from high-dimensional data based on combinatorial computation
Finished by March 31, 2014

Against the backdrop of accelerating progress of data acquisition technologies, there are more scenes where we deal with high-dimensional data in a variety of engineering problems, such as bioinformatics, natural language processing and image data processing. The purpose of this research is to build a data-mining framework for global analysis of high-dimensional data based on combinatorial computation, using the discrete data structure called submodularity. And, we aim at discovering important knowledge in a variety of applications by applying the developed algorithms to real-world data.