I collected here the list of my write-ups of the first three keynote speeches of the conference: Human in the Loop Machine Learning (Carla E. Brodley, Northeastern Univ.) Enhancing Human Perception via Text Mining and IR (Cheng Zhai, Univ. Illinois) Graph Representation Learning (Jure Leskovec, Stanford and Pinterest)
Over one billion cars interact with each other on the road every day. Each driver has his own driving style, which could impact safety, fuel economy and road congestion. Knowledge about the driving style of the driver could be used to encourage “better” driving behaviour through immediate feedback while driving, or by scaling auto insurance … Continue reading Driving Style and Behavior Analysis based on Trip Segmentation over GPS Information through Unsupervised Learning
FaST – Fashion Sensing Technology – is a project meant to design, experiment with, and implement an ICT tool that could monitor and analyze the activity of Italian emerging Fashion brands on social media.
Improving the quality of the language notation may improve dramatically acceptance and adoption, as well as the way people use your notation and the associated tools. Here is a systematic (and automatic) method for creating crowdsourcing campaigns aimed at refining the graphical notation of domain-specific languages.