One challenge faced by many Inductive Logic Programming (ILP) systems is poor scalability to problems with large search spaces and many examples. Randomized search methods such as ...
We present a novel approach to machine learning, called ABML (argumentation based ML). This approach combines machine learning from examples with concepts from the field of argum...
— Assisting humans in their daily lives requires robots to be proficient in manual tasks and effective in communicating states/intentions with human users. This paper advocates ...
In a previous study ([4]), we used the ASSISTment system to track student knowledge longitudinally over the course of a schools year, based upon each student using our system about...
Mingyu Feng, Neil T. Heffernan, Joseph E. Beck, Ke...
We present a general machine learning framework for modelling the phenomenon of missing information in data. We propose a masking process model to capture the stochastic nature of...