102 citations · 430 across the 25 of their papers we have counts for
5 papers · 1 filter
A Modular Theory of Feature Learning
Daniel McNamara, Cheng Soon Ong, Robert C. Williamson
Learning representations of data, and in particular learning features for a subsequent prediction task, has been a fruitful area of research delivering impressive empirical results…
Hawkes Processes with Stochastic Excitations
Young Lee, Kar Wai Lim, Cheng Soon Ong
We propose an extension to Hawkes processes by treating the levels of self-excitation as a stochastic differential equation. Our new point process allows better approximation in ap…
Probabilistic Knowledge Graph Construction: Compositional and Incremental Approaches
Dongwoo Kim, Lexing Xie, Cheng Soon Ong
Knowledge graph construction consists of two tasks: extracting information from external resources (knowledge population) and inferring missing information through a statistical an…
Learning Points and Routes to Recommend Trajectories
Dawei Chen, Cheng Soon Ong, Lexing Xie
The problem of recommending tours to travellers is an important and broadly studied area. Suggested solutions include various approaches of points-of-interest (POI) recommendation…
A scaled Bregman theorem with applications
Richard Nock, Aditya Krishna Menon, Cheng Soon Ong
Bregman divergences play a central role in the design and analysis of a range of machine learning algorithms. This paper explores the use of Bregman divergences to establish reduct…