1 code implementation • CVPR 2019 • Anand Gopalakrishnan, Ankur Mali, Dan Kifer, C. Lee Giles, Alexander G. Ororbia
We propose novel neural temporal models for predicting and synthesizing human motion, achieving state-of-the-art in modeling long-term motion trajectories while being competitive with prior work in short-term prediction and requiring significantly less computation.
no code implementations • 22 Nov 2016 • Xiao Yang, Dafang He, Wenyi Huang, Zihan Zhou, Alex Ororbia, Dan Kifer, C. Lee Giles
Physical library collections are valuable and long standing resources for knowledge and learning.
no code implementations • 28 Dec 2015 • Hongjian Wang, Zhenhui Li, Yu-Hsuan Kuo, Dan Kifer
The increased availability of large-scale trajectory data around the world provides rich information for the study of urban dynamics.
no code implementations • 24 Nov 2015 • Vishesh Karwa, Dan Kifer, Aleksandra B. Slavković
We focus on estimating posterior distributions of parameters of the naive Bayes log-linear model, where the sufficient statistics of this model are shared using a differentially private interface.