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Systems for declarative large-scale machine learning (ML) algorithms aim at high-level algorithm specification and automatic optimization of runtime execution plans. State-of-the-art compilers rely on algebraic rewrites and operator selection , including fused operators to avoid materialized in-termediates, reduce memory bandwidth requirements, and exploit(More)
Producing high-quality stereoscopic 3D content requires significantly more effort than preparing regular video footage. In order to assure good depth perception and visual comfort, 3D videos need to be carefully adjusted to specific viewing conditions before they are shown to viewers. While most stereoscopic 3D content is designed for viewing in movie(More)
Web sites, social networks, sensors, and scientific experiments currently generate massive amounts of data. Owners of this data strive to obtain insights from it, often by applying machine learning algorithms. Many machine learning algorithms, however, do not scale well to cope with the ever increasing volumes of data. To address this problem, we identify(More)
Three dimensional (3D) content is becoming attractive in entertainment events such as soccer games and movies. Also, 3D displays are widespread at homes, offices, and theaters. Yet, 3D content may lack good 3D experience due to varying display technologies and sizes. In addition, 3D content providers may not be able to deliver their content to all potential(More)
Current three-dimensional displays cannot fully reproduce all depth cues used by a human observer in the real world. Instead, they create only an illusion of looking at a three-dimensional scene. This leads to a number of challenges during the content creation process. To assure correct depth reproduction and visual comfort, either the acquisition setup has(More)
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