Exponential Families for Conditional Random Fields

2012/07/11 by Yasemin Altün, Alex Smola, Altun, Yasemin +3 · 1 citation
Computer Science · #Bayesian Methods and Mixture Models #Bayesian Modeling and Causal Inference #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML)

paper · pdf · doi:10.48550/arxiv.1207.4131

openalex publication_date 2012/07/11 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

In this paper we de ne conditional random elds in reproducing kernel Hilbert spaces and show connections to Gaussian Process classi cation. More speci cally, we prove decomposition results for undirected graphical models and we give constructions for kernels. Finally we present e cient means of solving the optimization problem using reduced rank decompositions and we show how stationarity can be exploited e ciently in the optimization process.

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