In supervised machine learning, variable ranking aims at sorting the input variables according to their relevance w.r.t. an output variable. In this paper, we propose a new relevan...
Real-world relational data are seldom stationary, yet traditional collaborative filtering algorithms generally rely on this assumption. Motivated by our sales prediction problem, ...
Liang Xiong, Xi Chen, Tzu-Kuo Huang, Jeff Schneide...
Many real world applications employ multivariate performance measures and each example can belong to multiple classes. The currently most popular approaches train an SVM for each ...
Abstract. The Bayesian approach to machine learning amounts to inferring posterior distributions of random variables from a probabilistic model of how the variables are related (th...
We introduce the Spherical Admixture Model (SAM), a Bayesian topic model for arbitrary 2 normalized data. SAM maintains the same hierarchical structure as Latent Dirichlet Allocat...
Joseph Reisinger, Austin Waters, Bryan Silverthorn...