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You searched for +publisher:"University of Texas – Austin" +contributor:("Rajan, Suju"). One record found.

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1. -3023-4337. Knowledge transfer using latent variable models.

Degree: Electrical and Computer Engineering, 2015, University of Texas – Austin

In several applications, scarcity of labeled data is a challenging problem that hinders the predictive capabilities of machine learning algorithms. Additionally, the distribution of the data changes over time, rendering models trained with older data less capable of discovering useful structure from the newly available data. Transfer learning is a convenient framework to overcome such problems where the learning of a model specific to a domain can benefit the learning of other models in other domains through either simultaneous training of domains or sequential transfer of knowledge from one domain to the others. This thesis explores the opportunities of knowledge transfer in the context of a few applications pertaining to object recognition from images, text analysis, network modeling and recommender systems, using probabilistic latent variable models as building blocks. Both simultaneous and sequential knowledge transfer are achieved through the latent variables, either by sharing these across multiple related domains (for simultaneous learning) or by adapting their distributions to fit data from a new domain (for sequential learning). Advisors/Committee Members: Ghosh, Joydeep (advisor), Mooney, Raymond J. (Raymond Joseph) (advisor), Shakkottai, Sanjay (committee member), Sanghavi, Sujay (committee member), Rajan, Suju (committee member).

Subjects/Keywords: Transfer learning; Multitask learning; Gamma process; Poisson factorization; Supervised topic model

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APA (6th Edition):

-3023-4337. (2015). Knowledge transfer using latent variable models. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/31414

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

-3023-4337. “Knowledge transfer using latent variable models.” 2015. Thesis, University of Texas – Austin. Accessed March 19, 2019. http://hdl.handle.net/2152/31414.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

-3023-4337. “Knowledge transfer using latent variable models.” 2015. Web. 19 Mar 2019.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Vancouver:

-3023-4337. Knowledge transfer using latent variable models. [Internet] [Thesis]. University of Texas – Austin; 2015. [cited 2019 Mar 19]. Available from: http://hdl.handle.net/2152/31414.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

-3023-4337. Knowledge transfer using latent variable models. [Thesis]. University of Texas – Austin; 2015. Available from: http://hdl.handle.net/2152/31414

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete
Not specified: Masters Thesis or Doctoral Dissertation

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