Hierarchical probabilistic modeling of discrete data has emerged as a powerful tool for text analysis. Posterior inference in such models is intractable, and practitioners rely on...
This paper presents a theoretical analysis of the problem of domain adaptation with multiple sources. For each source domain, the distribution over the input points as well as a h...
for ideas, and then abstract away from these ideas to produce algorithmic processes that can create problem solutions in a bottom-up manner. We have previously described a top-dow...
Abstract. We present a probabilistic algorithm for finding correspondences across multiple images. The algorithm runs in a distributed setting, where each camera is attached to a s...
While discriminative training (e.g., CRF, structural SVM) holds much promise for machine translation, image segmentation, and clustering, the complex inference these applications ...