Most typical statistical and machine learning approaches to time series modeling optimize a singlestep prediction error. In multiple-step simulation, the learned model is iterativ...
Arun Venkatraman, Martial Hebert, J. Andrew Bagnel...
We present an approach to incorporate interesting and compelling characters in planning-based narrative generation. The approach is based on a computational model that utilizes ch...
The expressive power of a Gaussian process (GP) model comes at a cost of poor scalability in the data size. To improve its scalability, this paper presents a low-rank-cum-Markov a...
Kian Hsiang Low, Jiangbo Yu, Jie Chen, Patrick Jai...
Covariate shift correction allows one to perform inference even when the distribution of the covariates on the training set does not match those on the test set. This is achieved ...