17th IEEE International Conference on Machine Learning and Applications
IEEE’s ICMLA 2018 (International Conference on Machine Learning and Applications) held December 17-20, in Orlando FL, aimed to bring together researchers and practitioners to present their latest achievements and innovations in the area of machine learning (ML). The Conference provided an international forum for the dissemination of original research in ML, with emphasis on applications as well as novel algorithms and systems. Following the success of previous ICMLA conferences, the Conference aimed to attract researchers and application developers from a wide range of ML related areas as the recent emergence of Big Data processing brings an urgent need for machine learning to address these new challenges. The Conference covered both machine learning theoretical research and its applications. Contributions describing machine learning techniques applied to real-world problems and interdisciplinary research involving machine learning, in fields like medicine, biology, industry, manufacturing, security, education, virtual environments, games, were especially encouraged.
Participants included CCS’s Big Data Analytics and Data Mining Program Director Mitsu Ogihara and Postdoctoral Associate Gang Ren, who attended the Conference and presented their paper (#585) as part of Special Session: Machine Learning Algorithms, Systems, and Applications (Short Papers): “The Semantic Shapes of Popular Music Lyrics: Graph-Based Representation, Analysis, and Interpretation of Popular Music Lyrics in Semantic Natural Language Embedding Space” (authors: Mitsunori Ogihara, Daniel Galarraga, Gang Ren, and Tiago Tavares).
M. Ogihara, D. Galarraga, G. Ren and T. Tavares, The Semantic Shapes of Popular Music Lyrics: Graph-Based Representation, Analysis, and Interpretation of Popular Music Lyrics in Semantic Natural Language Embedding Space, 2018 17th IEEE International Conference on Machine Learning and Applications (ICMLA), Orlando, FL, 2018, pp. 1249-1254, doi: 10.1109/ICMLA.2018.00203.