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DSMML
2004
Springer
13 years 10 months ago
Understanding Gaussian Process Regression Using the Equivalent Kernel
The equivalent kernel [1] is a way of understanding how Gaussian process regression works for large sample sizes based on a continuum limit. In this paper we show how to approximat...
Peter Sollich, Christopher K. I. Williams
NIPS
2004
13 years 6 months ago
Using the Equivalent Kernel to Understand Gaussian Process Regression
The equivalent kernel [1] is a way of understanding how Gaussian process regression works for large sample sizes based on a continuum limit. In this paper we show (1) how to appro...
Peter Sollich, Christopher K. I. Williams
NIPS
2007
13 years 6 months ago
Using Deep Belief Nets to Learn Covariance Kernels for Gaussian Processes
We show how to use unlabeled data and a deep belief net (DBN) to learn a good covariance kernel for a Gaussian process. We first learn a deep generative model of the unlabeled da...
Ruslan Salakhutdinov, Geoffrey E. Hinton
SDM
2009
SIAM
172views Data Mining» more  SDM 2009»
14 years 2 months ago
Travel-Time Prediction Using Gaussian Process Regression: A Trajectory-Based Approach.
This paper is concerned with the task of travel-time prediction for an arbitrary origin-destination pair on a map. Unlike most of the existing studies, which focus only on a parti...
Sei Kato, Tsuyoshi Idé
NIPS
2001
13 years 6 months ago
Learning a Gaussian Process Prior for Automatically Generating Music Playlists
This paper presents AutoDJ: a system for automatically generating music playlists based on one or more seed songs selected by a user. AutoDJ uses Gaussian Process Regression to le...
John C. Platt, Christopher J. C. Burges, S. Swenso...