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You searched for +publisher:"University of Texas – Austin" +contributor:("Huang, Qixing"). Showing records 1 – 7 of 7 total matches.

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1. -7041-9136. Evolutionary neural architecture search for deep learning.

Degree: PhD, Computer Science, 2019, University of Texas – Austin

 Deep neural networks (DNNs) have produced state-of-the-art results in many benchmarks and problem domains. However, the success of DNNs depends on the proper configuration of… (more)

Subjects/Keywords: Neural architecture search; Deep learning; Neuroevolution; Evolutionary computation; Artificial intelligence

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

-7041-9136. (2019). Evolutionary neural architecture search for deep learning. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://dx.doi.org/10.26153/tsw/1388

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

Chicago Manual of Style (16th Edition):

-7041-9136. “Evolutionary neural architecture search for deep learning.” 2019. Doctoral Dissertation, University of Texas – Austin. Accessed September 29, 2020. http://dx.doi.org/10.26153/tsw/1388.

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

MLA Handbook (7th Edition):

-7041-9136. “Evolutionary neural architecture search for deep learning.” 2019. Web. 29 Sep 2020.

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

Vancouver:

-7041-9136. Evolutionary neural architecture search for deep learning. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2019. [cited 2020 Sep 29]. Available from: http://dx.doi.org/10.26153/tsw/1388.

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

Council of Science Editors:

-7041-9136. Evolutionary neural architecture search for deep learning. [Doctoral Dissertation]. University of Texas – Austin; 2019. Available from: http://dx.doi.org/10.26153/tsw/1388

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

2. -5349-4575. Stochastic gradients methods for statistical inference.

Degree: PhD, Computer Science, 2019, University of Texas – Austin

 Statistical inference, such as hypothesis testing and calculating a confidence interval, is an important tool for accessing uncertainty in machine learning and statistical problems. Stochastic… (more)

Subjects/Keywords: Statistical inference; Stochastic gradient; M-estimation; High dimensional statistics; Time series

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APA (6th Edition):

-5349-4575. (2019). Stochastic gradients methods for statistical inference. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://dx.doi.org/10.26153/tsw/2200

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

Chicago Manual of Style (16th Edition):

-5349-4575. “Stochastic gradients methods for statistical inference.” 2019. Doctoral Dissertation, University of Texas – Austin. Accessed September 29, 2020. http://dx.doi.org/10.26153/tsw/2200.

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

MLA Handbook (7th Edition):

-5349-4575. “Stochastic gradients methods for statistical inference.” 2019. Web. 29 Sep 2020.

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

Vancouver:

-5349-4575. Stochastic gradients methods for statistical inference. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2019. [cited 2020 Sep 29]. Available from: http://dx.doi.org/10.26153/tsw/2200.

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

Council of Science Editors:

-5349-4575. Stochastic gradients methods for statistical inference. [Doctoral Dissertation]. University of Texas – Austin; 2019. Available from: http://dx.doi.org/10.26153/tsw/2200

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

3. -4493-3358. Appropriate, accessible and appealing probabilistic graphical models.

Degree: PhD, Computer Science, 2017, University of Texas – Austin

 Appropriate - Many multivariate probabilistic models either use independent distributions or dependent Gaussian distributions. Yet, many real-world datasets contain count-valued or non-negative skewed data, e.g.… (more)

Subjects/Keywords: Graphical models; Topic models; Poisson; Count data; Visualization; Human computer interaction

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APA (6th Edition):

-4493-3358. (2017). Appropriate, accessible and appealing probabilistic graphical models. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/62986

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

Chicago Manual of Style (16th Edition):

-4493-3358. “Appropriate, accessible and appealing probabilistic graphical models.” 2017. Doctoral Dissertation, University of Texas – Austin. Accessed September 29, 2020. http://hdl.handle.net/2152/62986.

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

MLA Handbook (7th Edition):

-4493-3358. “Appropriate, accessible and appealing probabilistic graphical models.” 2017. Web. 29 Sep 2020.

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

Vancouver:

-4493-3358. Appropriate, accessible and appealing probabilistic graphical models. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2017. [cited 2020 Sep 29]. Available from: http://hdl.handle.net/2152/62986.

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

Council of Science Editors:

-4493-3358. Appropriate, accessible and appealing probabilistic graphical models. [Doctoral Dissertation]. University of Texas – Austin; 2017. Available from: http://hdl.handle.net/2152/62986

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


University of Texas – Austin

4. Yu, Aron Yingbo. Fine-grained visual comparisons.

Degree: PhD, Electrical and Computer Engineering, 2019, University of Texas – Austin

 Beyond recognizing objects, a computer vision system ought to be able to compare them. A promising way to represent visual comparisons is through attributes, which… (more)

Subjects/Keywords: Computer vision; Visual search; Fine-grained; Ranking; Comparison; Attributes

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Yu, A. Y. (2019). Fine-grained visual comparisons. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://dx.doi.org/10.26153/tsw/5810

Chicago Manual of Style (16th Edition):

Yu, Aron Yingbo. “Fine-grained visual comparisons.” 2019. Doctoral Dissertation, University of Texas – Austin. Accessed September 29, 2020. http://dx.doi.org/10.26153/tsw/5810.

MLA Handbook (7th Edition):

Yu, Aron Yingbo. “Fine-grained visual comparisons.” 2019. Web. 29 Sep 2020.

Vancouver:

Yu AY. Fine-grained visual comparisons. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2019. [cited 2020 Sep 29]. Available from: http://dx.doi.org/10.26153/tsw/5810.

Council of Science Editors:

Yu AY. Fine-grained visual comparisons. [Doctoral Dissertation]. University of Texas – Austin; 2019. Available from: http://dx.doi.org/10.26153/tsw/5810


University of Texas – Austin

5. -2711-6738. Learning for 360° video compression, recognition, and display.

Degree: PhD, Computer Science, 2019, University of Texas – Austin

 360° cameras are a core building block of the Virtual Reality (VR) and Augmented Reality (AR) technology that bridges the real and digital worlds. It… (more)

Subjects/Keywords: 360° video; Omnidirectional media; Video analysis

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

-2711-6738. (2019). Learning for 360° video compression, recognition, and display. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://dx.doi.org/10.26153/tsw/5848

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

Chicago Manual of Style (16th Edition):

-2711-6738. “Learning for 360° video compression, recognition, and display.” 2019. Doctoral Dissertation, University of Texas – Austin. Accessed September 29, 2020. http://dx.doi.org/10.26153/tsw/5848.

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

MLA Handbook (7th Edition):

-2711-6738. “Learning for 360° video compression, recognition, and display.” 2019. Web. 29 Sep 2020.

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

Vancouver:

-2711-6738. Learning for 360° video compression, recognition, and display. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2019. [cited 2020 Sep 29]. Available from: http://dx.doi.org/10.26153/tsw/5848.

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

Council of Science Editors:

-2711-6738. Learning for 360° video compression, recognition, and display. [Doctoral Dissertation]. University of Texas – Austin; 2019. Available from: http://dx.doi.org/10.26153/tsw/5848

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


University of Texas – Austin

6. Xiong, Bo. Learning to compose photos and videos from passive cameras.

Degree: PhD, Computer Science, 2019, University of Texas – Austin

 Photo and video overload is well-known to most computer users. With cameras on mobile devices, it is all too easy to snap images and videos… (more)

Subjects/Keywords: Passive cameras; Video highlight detection; Snap point detection; Image segmentation; Video segmentation; Viewing panoramas

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Xiong, B. (2019). Learning to compose photos and videos from passive cameras. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://dx.doi.org/10.26153/tsw/5847

Chicago Manual of Style (16th Edition):

Xiong, Bo. “Learning to compose photos and videos from passive cameras.” 2019. Doctoral Dissertation, University of Texas – Austin. Accessed September 29, 2020. http://dx.doi.org/10.26153/tsw/5847.

MLA Handbook (7th Edition):

Xiong, Bo. “Learning to compose photos and videos from passive cameras.” 2019. Web. 29 Sep 2020.

Vancouver:

Xiong B. Learning to compose photos and videos from passive cameras. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2019. [cited 2020 Sep 29]. Available from: http://dx.doi.org/10.26153/tsw/5847.

Council of Science Editors:

Xiong B. Learning to compose photos and videos from passive cameras. [Doctoral Dissertation]. University of Texas – Austin; 2019. Available from: http://dx.doi.org/10.26153/tsw/5847


University of Texas – Austin

7. -1801-9896. Perceptual monocular depth estimation.

Degree: PhD, Electrical and Computer Engineering, 2020, University of Texas – Austin

 Monocular depth estimation (MDE), which is the task of using a single image to predict scene depths, has gained considerable interest, in large part owing… (more)

Subjects/Keywords: Monocular depth estimation; Natural scene statistics; Depth estimation; Perceptual depth estimation; Bivariate natural scene statistics; Bivariate correlation

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

-1801-9896. (2020). Perceptual monocular depth estimation. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://dx.doi.org/10.26153/tsw/8461

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

Chicago Manual of Style (16th Edition):

-1801-9896. “Perceptual monocular depth estimation.” 2020. Doctoral Dissertation, University of Texas – Austin. Accessed September 29, 2020. http://dx.doi.org/10.26153/tsw/8461.

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

MLA Handbook (7th Edition):

-1801-9896. “Perceptual monocular depth estimation.” 2020. Web. 29 Sep 2020.

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

Vancouver:

-1801-9896. Perceptual monocular depth estimation. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2020. [cited 2020 Sep 29]. Available from: http://dx.doi.org/10.26153/tsw/8461.

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

Council of Science Editors:

-1801-9896. Perceptual monocular depth estimation. [Doctoral Dissertation]. University of Texas – Austin; 2020. Available from: http://dx.doi.org/10.26153/tsw/8461

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

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