Reinforcement learning is a paradigm under which an agent seeks to improve its policy by making learning updates based on the experiences it gathers through interaction with the en...
This paper presents an interactive transfer function design tool based on ellipsoidal Gaussian transfer functions (ETFs). Our approach explores volumetric features in the statisti...
Contemporary product design and process development is based on an iterative specify-evaluate-revise approach which is often time intensive and therein non-responsive to customer ...
Max Blair, Steven R. LeClair, Jeffrey V. Zweber, A...
Work-integrated learning (WIL) poses unique challenges for user model design: on the one hand users’ knowledge levels need to be determined based on their work activities – tes...
Characterized by simultaneous measurement of the effects of experimental factors and their interactions, the economic and efficient factorial design is well accepted in microarray ...
Qihua Tan, Jesper Dahlgaard, Basem M. Abdallah, We...