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Eric P. Xing
Researcher at Carnegie Mellon University
Publications - 725
Citations - 48035
Eric P. Xing is an academic researcher from Carnegie Mellon University. The author has contributed to research in topics: Inference & Topic model. The author has an hindex of 99, co-authored 711 publications receiving 41467 citations. Previous affiliations of Eric P. Xing include Microsoft & Intel.
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Proceedings Article
Distance Metric Learning with Application to Clustering with Side-Information
TL;DR: This paper presents an algorithm that, given examples of similar (and, if desired, dissimilar) pairs of points in �”n, learns a distance metric over ℝn that respects these relationships.
Journal ArticleDOI
Mixed Membership Stochastic Blockmodels
TL;DR: In this article, the authors introduce a class of variance allocation models for pairwise measurements, called mixed membership stochastic blockmodels, which combine global parameters that instantiate dense patches of connectivity (blockmodel) with local parameters (mixed membership), and develop a general variational inference algorithm for fast approximate posterior inference.
Posted Content
Mixed membership stochastic blockmodels
TL;DR: The mixed membership stochastic block model as discussed by the authors extends block models for relational data to ones which capture mixed membership latent relational structure, thus providing an object-specific low-dimensional representation.
Proceedings ArticleDOI
Object Bank: A High-Level Image Representation for Scene Classification & Semantic Feature Sparsification
TL;DR: A high-level image representation, called the Object Bank, is proposed, where an image is represented as a scale-invariant response map of a large number of pre-trained generic object detectors, blind to the testing dataset or visual task.
Proceedings Article
Toward controlled generation of text
TL;DR: A new neural generative model is proposed which combines variational auto-encoders and holistic attribute discriminators for effective imposition of semantic structures inGeneric generation and manipulation of text.