Infinite Mixture of Global Gaussian Processes

  • Perez-Cruz F.
  • Pradier M.

In this paper, we propose a simple and powerful approach to solve nonlinear regression problems using an infinite mixture of global Gaussian processes (IMoGGP). Our method is able to deal with arbitrary output distributions, nonstationary signals, heteroscedastic noise and multimodal predictive distributions straightforwardly, without the modeler needing to know these attributes a priori. The IMoGGP can be interpreted as a mixture of experts, in which the experts are not local and they cooperate in the whole input space to provide accurate regression estimates. It can also be framed as a Dependent Dirichlet Process to solve discriminative tasks. Simulations show that our method gives comparative results to state-of-the-art approaches and its simplicity makes it an attractive method for non-ML-expert practitioners that do not want to rely on many different models to test which one fits their data best.

Recent Publications

January 01, 2019

Friendly, appealing or both? Characterising user experience in sponsored search landing pages

  • Bron M.
  • Chute M.
  • Evans H.
  • Lalmas M.
  • Redi M.
  • Silvestri F.

© 2017 International World Wide Web Conference Committee (IW3C2), published under Creative Commons CC BY 4.0 License. Many of today's websites have recognised the importance of mobile friendly pages to keep users engaged and to provide a satisfying user experience. However, next to the experience provided by the sites themselves, ...

January 01, 2019

Analyzing uber's ride-sharing economy

  • Aiello L.
  • Djuric N.
  • Grbovic M.
  • Kooti F.
  • Lerman K.
  • Radosavljevic V.

© 2017 International World Wide Web Conference Committee (IW3C2), published under Creative Commons CC BY 4.0 License. Uber is a popular ride-sharing application that matches people who need a ride (or riders) with drivers who are willing to provide it using their personal vehicles. Despite its growing popularity, there exist ...

January 01, 2019

The paradigm-shift of social spambots: Evidence, theories, and tools for the arms race

  • Cresci S.
  • Petrocchi M.
  • Pietro R.
  • Spognardi A.
  • Tesconi M.

© 2017 International World Wide Web Conference Committee (IW3C2), published under Creative Commons CC BY 4.0 License. Recent studies in social media spam and automation provide anecdotal argumentation of the rise of a new generation of spambots, so-called social spambots. Here, for the first time, we extensively study this novel ...