The Gaussian process latent variable model (GP-LVM) is a powerful approach for probabilistic modelling of high dimensional data through dimensional reduction. In this paper we ext...
Abstract--We quantify the closeness of the approximation between two high-level probabilistic models of cascading failure. In one model called CASCADE, failing components successiv...
— The protein structure prediction (PSP) problem is one of the most important problems in computational biology. This paper proposes a novel Estimation of Distribution Algorithms...
We explore unsupervised approaches to relation extraction between two named entities; for instance, the semantic bornIn relation between a person and location entity. Concretely, ...
Limin Yao, Aria Haghighi, Sebastian Riedel, Andrew...
To better serve users’ information needs without requiring comprehensive queries from users, a simple yet effective technique is to explore the preferences of users. Since these...
Arthur H. van Bunningen, Maarten M. Fokkinga, Pete...