Now showing items 1-3 of 3

    • APPLICATION OF THE TENSOR TRAIN DECOMPOSITION IN MACHINE LEARNING - A STUDY AND TRADEOFFS 

      Wilkinson, Andrew; 0000-0002-0237-1775 (State University of New York at Buffalo, 2019)
      Modern applications in machine learning are increasingly focused on large and distributed sets of data, which are often multidimensional in nature. Such multidimensional datasets are referred to as tensors. Developing ...
    • Approaches to Extract Deep Phenotypes from Clinical Data 

      Luong, Duc Thanh Anh; 0000-0003-4768-5089 (State University of New York at Buffalo, 2019)
      Computational phenotyping is an emerging topic in health informatics. An important catalyst of this emergence is the increasing volume of clinical data available for analysis. However, clinical data typically consists of ...
    • Flexible Data Management on Mobile Systems 

      Chandrashekhara, Sharath; 0000-0002-9952-320 (State University of New York at Buffalo, 2019)
      Mobile systems have gradually become the predominant platform for everyday computing, and their capabilities are getting powerful by the day. Apps on mobile systems employ sophisticated data management solutions by making ...