This dissertation explores the idea of applying machine learning technologies to help computer users find information and better organize electronic resources, by presenting the research work conducted in the following three applications: FolderPredictor, Stacking Recommendation Engines, and Integrating Learning and Reasoning.
FolderPredictor is an intelligent desktop software tool that helps...
This dissertation presents nonlinear terahertz (THz) properties of carbon nanomaterials investigated by time-resolved high-field THz spectroscopy. In order to determine THz characteristics of nanomaterials, we performed THz power spectrum measurement, THz raster imaging, THz time-domain spectroscopy (THz-TDS) and time-resolved pump-probe experiment on two different types of single layer graphene and...
Knowledge workers are struggling in the information flood. There is a growing interest in intelligent desktop environments that help knowledge workers organize their daily life. Intelligent desktop environments allow the desktop user to define a set of “activities” that characterize the user’s desktop work. These environments then attempt to identify...
This paper addresses the high model complexity and overconfident frame labeling of state-of-the-art (SOTA) action segmenters. Their complexity is typically justified by the need to sequentially refine action segmentation through multiple stages of a deep architecture. However, this multistage refinement does not take into account uncertainty of frame labeling predicted...