Recently, a huge mount of data is readily available through the Internet and various sensors, and machine learning technology for discovering underlying rules and acquiring useful knowledge gathers considerable attention. From the theoretical side, machine learning has close connection to basic information science paradigms such as information theory, statistics, computer science, and statistical physics. Thus, fundamental theory of machine learning is expected to be further developed through interdisciplinary collaboration. On the other hand, from the application side, machine learning technology plays an important role in various fields including signal processing, natural language processing, speech processing, image processing, biology, robot control, financial engineering, and data mining. These application areas possess high potential for real-world industry, and will be further expanded by sharing common methodological challenges.
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