This paper employs the network perspective to study patterns and structures of intraorganizational learning networks. The theoretical background draws from cognitive theories, the...
Deep belief networks are a powerful way to model complex probability distributions. However, it is difficult to learn the structure of a belief network, particularly one with hidd...
Ryan Prescott Adams, Hanna M. Wallach, Zoubin Ghah...
Smartphones connected to cellular networks are increasingly being used to access Internet-based services. Using data collected from smartphones running a popular location-based app...
Sipat Triukose, Sebastien Ardon, Anirban Mahanti, ...
This paperconsidersthe problem of representingcomplex systems that evolve stochastically over time. Dynamic Bayesian networks provide a compact representation for stochastic proce...
With the phenomenal success of networking sites (e.g., Facebook, Twitter and LinkedIn), social networks have drawn substantial attention. On online social networking sites, link r...
Zhijun Yin, Manish Gupta, Tim Weninger, Jiawei Han