Akhtar, Naveed; Mian, Ajmal; Porikli, Fatih
We propose to jointly learn a Discriminative Bayesian dictionary along a linear classifier using coupled Beta-Bernoulli Processes. Our representation model uses separate base measures for the dictionary and the classifier, but associates them to the class-specific training data using the same Bernoulli distributions. The Bernoulli distributions control the frequency with which the factors (e.g. dictionary atoms) are used in data representations, and they are inferred while accounting for the...[Show more]
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