A Multitask Point Process Predictive Model

By Wenzhao Lian, Ricardo Henao, Vinayak A. Rao, Joseph E. Lucas, Lawrence Carin. 2015

65 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Charu C. Aggarwal
2. Qiang Yang
3. Jiliang Tang
4. Yaochu Jin
5. Yu Zhang
6. Huan Liu
7. Suhang Wang
8. Xilu Wang

Citations in the corpus

• A Survey on Multi-Task Learning (2017, methodology): “When r equals 1, this model degenerates to a case where model parameters of different tasks share a prior, which is similar to several Bayesian MTL models such as [56], [57], [58] that are based on Gaussian processes and t processes.”
• Signed Network Embedding in Social Media (2017, background): “Second, in this work we demonstrate that the embedding can improve the performance of link prediction in signed social networks; hence we will investigate how the embedding benefits other signed network mining tasks such as node classification, sentiment analysis [36] and multitask learning [37].”
• Recent Advances in Bayesian Optimization (2022, methodology): “To facilitate efficient inference of the work [274], pseudo inputs are adopted to derive a sparse construction for the GP [158].”