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You searched for +publisher:"Rutgers University" +contributor:("Farach-Colton, Martin"). Showing records 1 – 8 of 8 total matches.

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Rutgers University

1. Tsai, Meng-Tsung, 1984-. On the algorithmic aspects of Turán's Theorem.

Degree: PhD, Computer Science, 2017, Rutgers University

Turán's Theorem gives an upper bound on the number of edges of n-node, Kr-free graphs, or equivalently it can be restated as that every n-node,… (more)

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APA (6th Edition):

Tsai, Meng-Tsung, 1. (2017). On the algorithmic aspects of Turán's Theorem. (Doctoral Dissertation). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/55752/

Chicago Manual of Style (16th Edition):

Tsai, Meng-Tsung, 1984-. “On the algorithmic aspects of Turán's Theorem.” 2017. Doctoral Dissertation, Rutgers University. Accessed October 27, 2020. https://rucore.libraries.rutgers.edu/rutgers-lib/55752/.

MLA Handbook (7th Edition):

Tsai, Meng-Tsung, 1984-. “On the algorithmic aspects of Turán's Theorem.” 2017. Web. 27 Oct 2020.

Vancouver:

Tsai, Meng-Tsung 1. On the algorithmic aspects of Turán's Theorem. [Internet] [Doctoral dissertation]. Rutgers University; 2017. [cited 2020 Oct 27]. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/55752/.

Council of Science Editors:

Tsai, Meng-Tsung 1. On the algorithmic aspects of Turán's Theorem. [Doctoral Dissertation]. Rutgers University; 2017. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/55752/


Rutgers University

2. Kruševskaja, Darja, 1982-. Observing and optimizing online ad assignments.

Degree: PhD, Computer Science, 2015, Rutgers University

The main focus of this thesis work is on optimization and observation of ad assignments in online ad markets. Online ad markets allocate billions of… (more)

Subjects/Keywords: Internet advertising

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APA (6th Edition):

Kruševskaja, Darja, 1. (2015). Observing and optimizing online ad assignments. (Doctoral Dissertation). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/48548/

Chicago Manual of Style (16th Edition):

Kruševskaja, Darja, 1982-. “Observing and optimizing online ad assignments.” 2015. Doctoral Dissertation, Rutgers University. Accessed October 27, 2020. https://rucore.libraries.rutgers.edu/rutgers-lib/48548/.

MLA Handbook (7th Edition):

Kruševskaja, Darja, 1982-. “Observing and optimizing online ad assignments.” 2015. Web. 27 Oct 2020.

Vancouver:

Kruševskaja, Darja 1. Observing and optimizing online ad assignments. [Internet] [Doctoral dissertation]. Rutgers University; 2015. [cited 2020 Oct 27]. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/48548/.

Council of Science Editors:

Kruševskaja, Darja 1. Observing and optimizing online ad assignments. [Doctoral Dissertation]. Rutgers University; 2015. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/48548/


Rutgers University

3. Mahmud, Md Pavel, 1981-. Reduced representations for efficient analysis of genomic data: from microarray to high-throughput sequencing.

Degree: PhD, Computer Science, 2014, Rutgers University

Since the genomics era has started in the ’70s, microarray technologies have been extensively used for biological applications such as gene expression profiling, copy number… (more)

Subjects/Keywords: Genomes – Analysis; Markov processes – Mathematical models; Bayesian statistical decision theory

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APA (6th Edition):

Mahmud, Md Pavel, 1. (2014). Reduced representations for efficient analysis of genomic data: from microarray to high-throughput sequencing. (Doctoral Dissertation). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/45336/

Chicago Manual of Style (16th Edition):

Mahmud, Md Pavel, 1981-. “Reduced representations for efficient analysis of genomic data: from microarray to high-throughput sequencing.” 2014. Doctoral Dissertation, Rutgers University. Accessed October 27, 2020. https://rucore.libraries.rutgers.edu/rutgers-lib/45336/.

MLA Handbook (7th Edition):

Mahmud, Md Pavel, 1981-. “Reduced representations for efficient analysis of genomic data: from microarray to high-throughput sequencing.” 2014. Web. 27 Oct 2020.

Vancouver:

Mahmud, Md Pavel 1. Reduced representations for efficient analysis of genomic data: from microarray to high-throughput sequencing. [Internet] [Doctoral dissertation]. Rutgers University; 2014. [cited 2020 Oct 27]. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/45336/.

Council of Science Editors:

Mahmud, Md Pavel 1. Reduced representations for efficient analysis of genomic data: from microarray to high-throughput sequencing. [Doctoral Dissertation]. Rutgers University; 2014. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/45336/


Rutgers University

4. Roy, Rajat Shuvro, 1983-. Improving genome assembly by identifying reliable sequencing data.

Degree: PhD, Computer Science, 2014, Rutgers University

De novo Genome assembly and k-mer frequency counting are two of the classical prob- lems of Bioinformatics. k-mer counting helps to identify genomic k-mers from… (more)

Subjects/Keywords: Genomes – Analysis; Gene amplification

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APA (6th Edition):

Roy, Rajat Shuvro, 1. (2014). Improving genome assembly by identifying reliable sequencing data. (Doctoral Dissertation). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/45449/

Chicago Manual of Style (16th Edition):

Roy, Rajat Shuvro, 1983-. “Improving genome assembly by identifying reliable sequencing data.” 2014. Doctoral Dissertation, Rutgers University. Accessed October 27, 2020. https://rucore.libraries.rutgers.edu/rutgers-lib/45449/.

MLA Handbook (7th Edition):

Roy, Rajat Shuvro, 1983-. “Improving genome assembly by identifying reliable sequencing data.” 2014. Web. 27 Oct 2020.

Vancouver:

Roy, Rajat Shuvro 1. Improving genome assembly by identifying reliable sequencing data. [Internet] [Doctoral dissertation]. Rutgers University; 2014. [cited 2020 Oct 27]. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/45449/.

Council of Science Editors:

Roy, Rajat Shuvro 1. Improving genome assembly by identifying reliable sequencing data. [Doctoral Dissertation]. Rutgers University; 2014. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/45449/


Rutgers University

5. Wiedenhoeft, John. Dynamically compressed Bayesian hidden Markov models using Haar wavelets.

Degree: PhD, Computer Science, 2018, Rutgers University

 Hidden Markov Models (HMM) are a powerful and ubiquitous tool for segmentation and labeling in bioinformatics and beyond. Classic techniques to infer suitable model parameters… (more)

Subjects/Keywords: Bayesian field theory; Hidden Markov models

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APA (6th Edition):

Wiedenhoeft, J. (2018). Dynamically compressed Bayesian hidden Markov models using Haar wavelets. (Doctoral Dissertation). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/59275/

Chicago Manual of Style (16th Edition):

Wiedenhoeft, John. “Dynamically compressed Bayesian hidden Markov models using Haar wavelets.” 2018. Doctoral Dissertation, Rutgers University. Accessed October 27, 2020. https://rucore.libraries.rutgers.edu/rutgers-lib/59275/.

MLA Handbook (7th Edition):

Wiedenhoeft, John. “Dynamically compressed Bayesian hidden Markov models using Haar wavelets.” 2018. Web. 27 Oct 2020.

Vancouver:

Wiedenhoeft J. Dynamically compressed Bayesian hidden Markov models using Haar wavelets. [Internet] [Doctoral dissertation]. Rutgers University; 2018. [cited 2020 Oct 27]. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/59275/.

Council of Science Editors:

Wiedenhoeft J. Dynamically compressed Bayesian hidden Markov models using Haar wavelets. [Doctoral Dissertation]. Rutgers University; 2018. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/59275/


Rutgers University

6. Mosteiro, Miguel. Upper and lower bounds in radio networks.

Degree: PhD, Computer Science, 2007, Rutgers University

 Sensor nodes are very weak computers that get distributed at random on a surface in order to achieve a large-scale sensing task. Once deployed, they… (more)

Subjects/Keywords: Sensor networks; Multisensor data fusion; Signal processing; Operator theory

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APA (6th Edition):

Mosteiro, M. (2007). Upper and lower bounds in radio networks. (Doctoral Dissertation). Rutgers University. Retrieved from http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.13483

Chicago Manual of Style (16th Edition):

Mosteiro, Miguel. “Upper and lower bounds in radio networks.” 2007. Doctoral Dissertation, Rutgers University. Accessed October 27, 2020. http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.13483.

MLA Handbook (7th Edition):

Mosteiro, Miguel. “Upper and lower bounds in radio networks.” 2007. Web. 27 Oct 2020.

Vancouver:

Mosteiro M. Upper and lower bounds in radio networks. [Internet] [Doctoral dissertation]. Rutgers University; 2007. [cited 2020 Oct 27]. Available from: http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.13483.

Council of Science Editors:

Mosteiro M. Upper and lower bounds in radio networks. [Doctoral Dissertation]. Rutgers University; 2007. Available from: http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.13483


Rutgers University

7. Fernandes, Rohan Jude. Algorithms and LP-duality based lower bounds in ad-hoc radio networks.

Degree: PhD, Computer Science, 2007, Rutgers University

An Ad-hoc Radio Network consists of nodes with no knowledge of its neighbors and knowledge of its own ID and n, the size of the… (more)

Subjects/Keywords: Sensor networks; Radio frequency

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APA (6th Edition):

Fernandes, R. J. (2007). Algorithms and LP-duality based lower bounds in ad-hoc radio networks. (Doctoral Dissertation). Rutgers University. Retrieved from http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.15842

Chicago Manual of Style (16th Edition):

Fernandes, Rohan Jude. “Algorithms and LP-duality based lower bounds in ad-hoc radio networks.” 2007. Doctoral Dissertation, Rutgers University. Accessed October 27, 2020. http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.15842.

MLA Handbook (7th Edition):

Fernandes, Rohan Jude. “Algorithms and LP-duality based lower bounds in ad-hoc radio networks.” 2007. Web. 27 Oct 2020.

Vancouver:

Fernandes RJ. Algorithms and LP-duality based lower bounds in ad-hoc radio networks. [Internet] [Doctoral dissertation]. Rutgers University; 2007. [cited 2020 Oct 27]. Available from: http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.15842.

Council of Science Editors:

Fernandes RJ. Algorithms and LP-duality based lower bounds in ad-hoc radio networks. [Doctoral Dissertation]. Rutgers University; 2007. Available from: http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.15842


Rutgers University

8. Huang, Yang, 1976-. Computational approaches to identifying molecular associations in high-throughput biological data.

Degree: PhD, Computer Science, 2007, Rutgers University

Biomolecules, such as proteins and nucleic acids, are the building blocks of living organisms. Their complex interactions and associations are the key to understanding the… (more)

Subjects/Keywords: Bioinformatics; Computational biology

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

APA (6th Edition):

Huang, Yang, 1. (2007). Computational approaches to identifying molecular associations in high-throughput biological data. (Doctoral Dissertation). Rutgers University. Retrieved from http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.16094

Chicago Manual of Style (16th Edition):

Huang, Yang, 1976-. “Computational approaches to identifying molecular associations in high-throughput biological data.” 2007. Doctoral Dissertation, Rutgers University. Accessed October 27, 2020. http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.16094.

MLA Handbook (7th Edition):

Huang, Yang, 1976-. “Computational approaches to identifying molecular associations in high-throughput biological data.” 2007. Web. 27 Oct 2020.

Vancouver:

Huang, Yang 1. Computational approaches to identifying molecular associations in high-throughput biological data. [Internet] [Doctoral dissertation]. Rutgers University; 2007. [cited 2020 Oct 27]. Available from: http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.16094.

Council of Science Editors:

Huang, Yang 1. Computational approaches to identifying molecular associations in high-throughput biological data. [Doctoral Dissertation]. Rutgers University; 2007. Available from: http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.16094

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