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From cvss
→Talk Abstracts Spring 2015
Related paper:
Related paper:
[http://www.cs.umd.edu/~ozdemir/papers/nips14_iibp.pdf A Probabilistic Framework for Multimodal Retrieval using Integrative Indian Buffet Process, NIPS 2014]
[http://www.cs.umd.edu/~ozdemir/papers/nips14_iibp.pdf A Probabilistic Framework for Multimodal Retrieval using Integrative Indian Buffet Process, NIPS 2014]
===Matrix Completion for Resolving Label Ambiguity===
Speaker: Ching-Hui Chen
Abstract: In real applications, data is not always explicitly-labeled. For instance, label ambiguity exists when we associate two persons appearing in a news photo with two names provided in the caption. We propose a matrix completion-based method for resolving ambiguity to predict the actual labels from the ambiguously labeled instances, and a standard supervised classifier can learn from the disambiguated labels to classify new data. We further generalize the method to handle the labeling constraints between instances when such prior knowledge is available. Compared to the state of the arts, our proposed framework achieves 2.9% improvement on the labeling accuracy of the Lost dataset and comparable performance on the Labeled Yahoo! News dataset.
Related paper:
Matrix Completion for Resolving Label Ambiguity, To appear in CVPR2015
==Past Semesters==
==Past Semesters==
