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You searched for +publisher:"Oregon State University" +contributor:("Fern, Xiaoli Z."). Showing records 1 – 7 of 7 total matches.

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Oregon State University

1. Liu, Liping. Machine Learning Methods for Computational Sustainability.

Degree: PhD, Computer Science, 2016, Oregon State University

 Maintaining the sustainability of the earth’s ecosystems has attracted much attention as these ecosystems are facing more and more pressure from human activities. Machine learning… (more)

Subjects/Keywords: machine learning; Machine learning

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APA (6th Edition):

Liu, L. (2016). Machine Learning Methods for Computational Sustainability. (Doctoral Dissertation). Oregon State University. Retrieved from http://hdl.handle.net/1957/59159

Chicago Manual of Style (16th Edition):

Liu, Liping. “Machine Learning Methods for Computational Sustainability.” 2016. Doctoral Dissertation, Oregon State University. Accessed April 24, 2019. http://hdl.handle.net/1957/59159.

MLA Handbook (7th Edition):

Liu, Liping. “Machine Learning Methods for Computational Sustainability.” 2016. Web. 24 Apr 2019.

Vancouver:

Liu L. Machine Learning Methods for Computational Sustainability. [Internet] [Doctoral dissertation]. Oregon State University; 2016. [cited 2019 Apr 24]. Available from: http://hdl.handle.net/1957/59159.

Council of Science Editors:

Liu L. Machine Learning Methods for Computational Sustainability. [Doctoral Dissertation]. Oregon State University; 2016. Available from: http://hdl.handle.net/1957/59159


Oregon State University

2. Narasimhan, Revathy. Simultaneous Segmentation and Classification of Bird Song Using CNN.

Degree: MS, Electrical and Computer Engineering, 2016, Oregon State University

 In bioacoustics, automatic animal voice detection and recognition from audio recordings is an emerging topic for animal preservation. Our research focuses on bird bioacoustics, where… (more)

Subjects/Keywords: Birdsongs  – Data processing

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APA (6th Edition):

Narasimhan, R. (2016). Simultaneous Segmentation and Classification of Bird Song Using CNN. (Masters Thesis). Oregon State University. Retrieved from http://hdl.handle.net/1957/60040

Chicago Manual of Style (16th Edition):

Narasimhan, Revathy. “Simultaneous Segmentation and Classification of Bird Song Using CNN.” 2016. Masters Thesis, Oregon State University. Accessed April 24, 2019. http://hdl.handle.net/1957/60040.

MLA Handbook (7th Edition):

Narasimhan, Revathy. “Simultaneous Segmentation and Classification of Bird Song Using CNN.” 2016. Web. 24 Apr 2019.

Vancouver:

Narasimhan R. Simultaneous Segmentation and Classification of Bird Song Using CNN. [Internet] [Masters thesis]. Oregon State University; 2016. [cited 2019 Apr 24]. Available from: http://hdl.handle.net/1957/60040.

Council of Science Editors:

Narasimhan R. Simultaneous Segmentation and Classification of Bird Song Using CNN. [Masters Thesis]. Oregon State University; 2016. Available from: http://hdl.handle.net/1957/60040


Oregon State University

3. Ghaeini, Mohammad Reza. Event Detection with Forward-Backward Recurrent Neural Networks.

Degree: MS, 2017, Oregon State University

 Automatic event extraction from natural text is an important and challenging task for natural language understanding. Traditional event detection methods heavily rely on manually engineered… (more)

Subjects/Keywords: Deep Learning

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APA (6th Edition):

Ghaeini, M. R. (2017). Event Detection with Forward-Backward Recurrent Neural Networks. (Masters Thesis). Oregon State University. Retrieved from http://hdl.handle.net/1957/61576

Chicago Manual of Style (16th Edition):

Ghaeini, Mohammad Reza. “Event Detection with Forward-Backward Recurrent Neural Networks.” 2017. Masters Thesis, Oregon State University. Accessed April 24, 2019. http://hdl.handle.net/1957/61576.

MLA Handbook (7th Edition):

Ghaeini, Mohammad Reza. “Event Detection with Forward-Backward Recurrent Neural Networks.” 2017. Web. 24 Apr 2019.

Vancouver:

Ghaeini MR. Event Detection with Forward-Backward Recurrent Neural Networks. [Internet] [Masters thesis]. Oregon State University; 2017. [cited 2019 Apr 24]. Available from: http://hdl.handle.net/1957/61576.

Council of Science Editors:

Ghaeini MR. Event Detection with Forward-Backward Recurrent Neural Networks. [Masters Thesis]. Oregon State University; 2017. Available from: http://hdl.handle.net/1957/61576

4. Xie, Jun. Learning greedy policies for the easy-first framework.

Degree: MS, Computer Science, 2014, Oregon State University

 Easy-first, a search-based structured prediction approach, has been applied to many NLP tasks including dependency parsing and coreference resolution. This approach employs a learned greedy… (more)

Subjects/Keywords: Structured Prediction; Machine learning

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APA (6th Edition):

Xie, J. (2014). Learning greedy policies for the easy-first framework. (Masters Thesis). Oregon State University. Retrieved from http://hdl.handle.net/1957/46790

Chicago Manual of Style (16th Edition):

Xie, Jun. “Learning greedy policies for the easy-first framework.” 2014. Masters Thesis, Oregon State University. Accessed April 24, 2019. http://hdl.handle.net/1957/46790.

MLA Handbook (7th Edition):

Xie, Jun. “Learning greedy policies for the easy-first framework.” 2014. Web. 24 Apr 2019.

Vancouver:

Xie J. Learning greedy policies for the easy-first framework. [Internet] [Masters thesis]. Oregon State University; 2014. [cited 2019 Apr 24]. Available from: http://hdl.handle.net/1957/46790.

Council of Science Editors:

Xie J. Learning greedy policies for the easy-first framework. [Masters Thesis]. Oregon State University; 2014. Available from: http://hdl.handle.net/1957/46790

5. Tjahja, Teresa V. Supervised Hierarchical Segmentation for Bird Bioacoustics.

Degree: MS, Computer Science, 2015, Oregon State University

 Bioacoustics analysis can be used to conduct environmental monitoring by detecting the presence of birds species. This analysis usually involves identifying the species from their… (more)

Subjects/Keywords: supervised segmentation; Bioacoustics

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APA (6th Edition):

Tjahja, T. V. (2015). Supervised Hierarchical Segmentation for Bird Bioacoustics. (Masters Thesis). Oregon State University. Retrieved from http://hdl.handle.net/1957/56051

Chicago Manual of Style (16th Edition):

Tjahja, Teresa V. “Supervised Hierarchical Segmentation for Bird Bioacoustics.” 2015. Masters Thesis, Oregon State University. Accessed April 24, 2019. http://hdl.handle.net/1957/56051.

MLA Handbook (7th Edition):

Tjahja, Teresa V. “Supervised Hierarchical Segmentation for Bird Bioacoustics.” 2015. Web. 24 Apr 2019.

Vancouver:

Tjahja TV. Supervised Hierarchical Segmentation for Bird Bioacoustics. [Internet] [Masters thesis]. Oregon State University; 2015. [cited 2019 Apr 24]. Available from: http://hdl.handle.net/1957/56051.

Council of Science Editors:

Tjahja TV. Supervised Hierarchical Segmentation for Bird Bioacoustics. [Masters Thesis]. Oregon State University; 2015. Available from: http://hdl.handle.net/1957/56051

6. Xiong, Sicheng. Active learning of constraints for semi-supervised clustering.

Degree: MS, Computer Science, 2013, Oregon State University

 Semi-supervised clustering aims to improve clustering performance by considering user supervision in the form of pairwise constraints. In this paper, we study the active learning… (more)

Subjects/Keywords: Active Learning; Cluster analysis

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APA (6th Edition):

Xiong, S. (2013). Active learning of constraints for semi-supervised clustering. (Masters Thesis). Oregon State University. Retrieved from http://hdl.handle.net/1957/38533

Chicago Manual of Style (16th Edition):

Xiong, Sicheng. “Active learning of constraints for semi-supervised clustering.” 2013. Masters Thesis, Oregon State University. Accessed April 24, 2019. http://hdl.handle.net/1957/38533.

MLA Handbook (7th Edition):

Xiong, Sicheng. “Active learning of constraints for semi-supervised clustering.” 2013. Web. 24 Apr 2019.

Vancouver:

Xiong S. Active learning of constraints for semi-supervised clustering. [Internet] [Masters thesis]. Oregon State University; 2013. [cited 2019 Apr 24]. Available from: http://hdl.handle.net/1957/38533.

Council of Science Editors:

Xiong S. Active learning of constraints for semi-supervised clustering. [Masters Thesis]. Oregon State University; 2013. Available from: http://hdl.handle.net/1957/38533

7. Azimi, Javad. Bayesian optimization with empirical constraints.

Degree: PhD, Computer Science, 2012, Oregon State University

 Bayesian Optimization (BO) methods are often used to optimize an unknown function f(•) that is costly to evaluate. They typically work in an iterative manner.… (more)

Subjects/Keywords: Bayesian Optimization; Mathematical optimization

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APA (6th Edition):

Azimi, J. (2012). Bayesian optimization with empirical constraints. (Doctoral Dissertation). Oregon State University. Retrieved from http://hdl.handle.net/1957/33664

Chicago Manual of Style (16th Edition):

Azimi, Javad. “Bayesian optimization with empirical constraints.” 2012. Doctoral Dissertation, Oregon State University. Accessed April 24, 2019. http://hdl.handle.net/1957/33664.

MLA Handbook (7th Edition):

Azimi, Javad. “Bayesian optimization with empirical constraints.” 2012. Web. 24 Apr 2019.

Vancouver:

Azimi J. Bayesian optimization with empirical constraints. [Internet] [Doctoral dissertation]. Oregon State University; 2012. [cited 2019 Apr 24]. Available from: http://hdl.handle.net/1957/33664.

Council of Science Editors:

Azimi J. Bayesian optimization with empirical constraints. [Doctoral Dissertation]. Oregon State University; 2012. Available from: http://hdl.handle.net/1957/33664

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