35 citations · 53 across the 7 of their papers we have counts for
4 papers · 1 filter
Model Selection for Production System via Automated Online Experiments
Zhenwen Dai, Praveen Chandar, Ghazal Fazelnia +2
A challenge that machine learning practitioners in the industry face is the task of selecting the best model to deploy in production. As a model is often an intermediate component…
Intrinsic Gaussian processes on complex constrained domains
Mu Niu, Pokman Cheung, Lizhen Lin +3
We propose a class of intrinsic Gaussian processes (in-GPs) for interpolation, regression and classification on manifolds with a primary focus on complex constrained domains or irr…
Efficient Modeling of Latent Information in Supervised Learning using Gaussian Processes
Zhenwen Dai, Mauricio A. Álvarez, Neil D. Lawrence
Often in machine learning, data are collected as a combination of multiple conditions, e.g., the voice recordings of multiple persons, each labeled with an ID. How could we build a…
Spike and Slab Gaussian Process Latent Variable Models
Zhenwen Dai, James Hensman, Neil Lawrence
The Gaussian process latent variable model (GP-LVM) is a popular approach to non-linear probabilistic dimensionality reduction. One design choice for the model is the number of lat…