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You searched for +publisher:"Brown University" +contributor:("Ramanan, Kavita"). Showing records 1 – 11 of 11 total matches.

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1. Cai, Yi. Analysis of An Interacting Particle Method for Rare Event Estimation.

Degree: PhD, Applied Mathematics, 2012, Brown University

 This thesis is a large deviations study for the performance of an interacting particle method for rare event estimation. The analysis is restricted to a… (more)

Subjects/Keywords: interacting particle system

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APA (6th Edition):

Cai, Y. (2012). Analysis of An Interacting Particle Method for Rare Event Estimation. (Doctoral Dissertation). Brown University. Retrieved from https://repository.library.brown.edu/studio/item/bdr:297522/

Chicago Manual of Style (16th Edition):

Cai, Yi. “Analysis of An Interacting Particle Method for Rare Event Estimation.” 2012. Doctoral Dissertation, Brown University. Accessed November 28, 2020. https://repository.library.brown.edu/studio/item/bdr:297522/.

MLA Handbook (7th Edition):

Cai, Yi. “Analysis of An Interacting Particle Method for Rare Event Estimation.” 2012. Web. 28 Nov 2020.

Vancouver:

Cai Y. Analysis of An Interacting Particle Method for Rare Event Estimation. [Internet] [Doctoral dissertation]. Brown University; 2012. [cited 2020 Nov 28]. Available from: https://repository.library.brown.edu/studio/item/bdr:297522/.

Council of Science Editors:

Cai Y. Analysis of An Interacting Particle Method for Rare Event Estimation. [Doctoral Dissertation]. Brown University; 2012. Available from: https://repository.library.brown.edu/studio/item/bdr:297522/

2. Setayeshgar, Leila. Large Deviations for a Feed-forward Network & Importance Sampling for a Single Server Priority Queue.

Degree: PhD, Applied Mathematics, 2012, Brown University

 This thesis considers a feed-forward network with a single server station serving jobs with multiple levels of priority. The service discipline is preemptive in that… (more)

Subjects/Keywords: Weak Convergence

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APA (6th Edition):

Setayeshgar, L. (2012). Large Deviations for a Feed-forward Network & Importance Sampling for a Single Server Priority Queue. (Doctoral Dissertation). Brown University. Retrieved from https://repository.library.brown.edu/studio/item/bdr:297528/

Chicago Manual of Style (16th Edition):

Setayeshgar, Leila. “Large Deviations for a Feed-forward Network & Importance Sampling for a Single Server Priority Queue.” 2012. Doctoral Dissertation, Brown University. Accessed November 28, 2020. https://repository.library.brown.edu/studio/item/bdr:297528/.

MLA Handbook (7th Edition):

Setayeshgar, Leila. “Large Deviations for a Feed-forward Network & Importance Sampling for a Single Server Priority Queue.” 2012. Web. 28 Nov 2020.

Vancouver:

Setayeshgar L. Large Deviations for a Feed-forward Network & Importance Sampling for a Single Server Priority Queue. [Internet] [Doctoral dissertation]. Brown University; 2012. [cited 2020 Nov 28]. Available from: https://repository.library.brown.edu/studio/item/bdr:297528/.

Council of Science Editors:

Setayeshgar L. Large Deviations for a Feed-forward Network & Importance Sampling for a Single Server Priority Queue. [Doctoral Dissertation]. Brown University; 2012. Available from: https://repository.library.brown.edu/studio/item/bdr:297528/

3. Aghajani, Mohammadreza. Infinite-Dimensional Scaling Limits of Stochastic Networks.

Degree: PhD, Applied Mathematics, 2016, Brown University

 Large-scale stochastic networks arise in a variety of real world applications such as telecommunications, service systems, computer networks, health care, and biological systems. Such networks… (more)

Subjects/Keywords: Stochastic Networks

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APA (6th Edition):

Aghajani, M. (2016). Infinite-Dimensional Scaling Limits of Stochastic Networks. (Doctoral Dissertation). Brown University. Retrieved from https://repository.library.brown.edu/studio/item/bdr:674202/

Chicago Manual of Style (16th Edition):

Aghajani, Mohammadreza. “Infinite-Dimensional Scaling Limits of Stochastic Networks.” 2016. Doctoral Dissertation, Brown University. Accessed November 28, 2020. https://repository.library.brown.edu/studio/item/bdr:674202/.

MLA Handbook (7th Edition):

Aghajani, Mohammadreza. “Infinite-Dimensional Scaling Limits of Stochastic Networks.” 2016. Web. 28 Nov 2020.

Vancouver:

Aghajani M. Infinite-Dimensional Scaling Limits of Stochastic Networks. [Internet] [Doctoral dissertation]. Brown University; 2016. [cited 2020 Nov 28]. Available from: https://repository.library.brown.edu/studio/item/bdr:674202/.

Council of Science Editors:

Aghajani M. Infinite-Dimensional Scaling Limits of Stochastic Networks. [Doctoral Dissertation]. Brown University; 2016. Available from: https://repository.library.brown.edu/studio/item/bdr:674202/

4. Lee, Chia Ying. Effective approximations of stochastic partial differential equations based on Wiener chaos expansions and the Malliavin calculus.

Degree: PhD, Applied Mathematics, 2011, Brown University

 This thesis studies the application of the Wiener chaos expansion in the analysis of stochastic partial differential equations (SPDEs). Specifically, linear parabolic SPDEs and the… (more)

Subjects/Keywords: Wiener chaos expansion

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APA (6th Edition):

Lee, C. Y. (2011). Effective approximations of stochastic partial differential equations based on Wiener chaos expansions and the Malliavin calculus. (Doctoral Dissertation). Brown University. Retrieved from https://repository.library.brown.edu/studio/item/bdr:11267/

Chicago Manual of Style (16th Edition):

Lee, Chia Ying. “Effective approximations of stochastic partial differential equations based on Wiener chaos expansions and the Malliavin calculus.” 2011. Doctoral Dissertation, Brown University. Accessed November 28, 2020. https://repository.library.brown.edu/studio/item/bdr:11267/.

MLA Handbook (7th Edition):

Lee, Chia Ying. “Effective approximations of stochastic partial differential equations based on Wiener chaos expansions and the Malliavin calculus.” 2011. Web. 28 Nov 2020.

Vancouver:

Lee CY. Effective approximations of stochastic partial differential equations based on Wiener chaos expansions and the Malliavin calculus. [Internet] [Doctoral dissertation]. Brown University; 2011. [cited 2020 Nov 28]. Available from: https://repository.library.brown.edu/studio/item/bdr:11267/.

Council of Science Editors:

Lee CY. Effective approximations of stochastic partial differential equations based on Wiener chaos expansions and the Malliavin calculus. [Doctoral Dissertation]. Brown University; 2011. Available from: https://repository.library.brown.edu/studio/item/bdr:11267/

5. Liu, Yufei. Large Deviations Rate Functions for the Empirical Measure: Explicit Formulas and an Application to Monte Carlo.

Degree: PhD, Applied Mathematics, 2013, Brown University

 In this thesis, we use the large deviations principle to characterize the rate of convergence of the empirical measures of Markov processes. An explicit formula… (more)

Subjects/Keywords: empirical measure

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APA (6th Edition):

Liu, Y. (2013). Large Deviations Rate Functions for the Empirical Measure: Explicit Formulas and an Application to Monte Carlo. (Doctoral Dissertation). Brown University. Retrieved from https://repository.library.brown.edu/studio/item/bdr:320522/

Chicago Manual of Style (16th Edition):

Liu, Yufei. “Large Deviations Rate Functions for the Empirical Measure: Explicit Formulas and an Application to Monte Carlo.” 2013. Doctoral Dissertation, Brown University. Accessed November 28, 2020. https://repository.library.brown.edu/studio/item/bdr:320522/.

MLA Handbook (7th Edition):

Liu, Yufei. “Large Deviations Rate Functions for the Empirical Measure: Explicit Formulas and an Application to Monte Carlo.” 2013. Web. 28 Nov 2020.

Vancouver:

Liu Y. Large Deviations Rate Functions for the Empirical Measure: Explicit Formulas and an Application to Monte Carlo. [Internet] [Doctoral dissertation]. Brown University; 2013. [cited 2020 Nov 28]. Available from: https://repository.library.brown.edu/studio/item/bdr:320522/.

Council of Science Editors:

Liu Y. Large Deviations Rate Functions for the Empirical Measure: Explicit Formulas and an Application to Monte Carlo. [Doctoral Dissertation]. Brown University; 2013. Available from: https://repository.library.brown.edu/studio/item/bdr:320522/

6. Kim, Steven Soon. Problems at the Interface of Probability and Convex Geometry: Random Projections and Constrained Processes.

Degree: Department of Applied Mathematics, 2017, Brown University

 Convex sets in high-dimensional linear spaces are classical objects of study that have long enjoyed rich connections with probability theory. Interest in these connections has… (more)

Subjects/Keywords: Applied mathematics

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APA (6th Edition):

Kim, S. S. (2017). Problems at the Interface of Probability and Convex Geometry: Random Projections and Constrained Processes. (Thesis). Brown University. Retrieved from https://repository.library.brown.edu/studio/item/bdr:733380/

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

Chicago Manual of Style (16th Edition):

Kim, Steven Soon. “Problems at the Interface of Probability and Convex Geometry: Random Projections and Constrained Processes.” 2017. Thesis, Brown University. Accessed November 28, 2020. https://repository.library.brown.edu/studio/item/bdr:733380/.

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

MLA Handbook (7th Edition):

Kim, Steven Soon. “Problems at the Interface of Probability and Convex Geometry: Random Projections and Constrained Processes.” 2017. Web. 28 Nov 2020.

Vancouver:

Kim SS. Problems at the Interface of Probability and Convex Geometry: Random Projections and Constrained Processes. [Internet] [Thesis]. Brown University; 2017. [cited 2020 Nov 28]. Available from: https://repository.library.brown.edu/studio/item/bdr:733380/.

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

Council of Science Editors:

Kim SS. Problems at the Interface of Probability and Convex Geometry: Random Projections and Constrained Processes. [Thesis]. Brown University; 2017. Available from: https://repository.library.brown.edu/studio/item/bdr:733380/

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

7. Li, Zhongyang. Vertex Models, Ising Models and Fisher Graphs.

Degree: PhD, Mathematics, 2011, Brown University

 In Chapter 1, we study planar ``vertex'' models, which are probability measures onedge subsets of a planar graph, satisfying certain constraints ateach vertex, examples including… (more)

Subjects/Keywords: Local Statistics

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APA (6th Edition):

Li, Z. (2011). Vertex Models, Ising Models and Fisher Graphs. (Doctoral Dissertation). Brown University. Retrieved from https://repository.library.brown.edu/studio/item/bdr:11314/

Chicago Manual of Style (16th Edition):

Li, Zhongyang. “Vertex Models, Ising Models and Fisher Graphs.” 2011. Doctoral Dissertation, Brown University. Accessed November 28, 2020. https://repository.library.brown.edu/studio/item/bdr:11314/.

MLA Handbook (7th Edition):

Li, Zhongyang. “Vertex Models, Ising Models and Fisher Graphs.” 2011. Web. 28 Nov 2020.

Vancouver:

Li Z. Vertex Models, Ising Models and Fisher Graphs. [Internet] [Doctoral dissertation]. Brown University; 2011. [cited 2020 Nov 28]. Available from: https://repository.library.brown.edu/studio/item/bdr:11314/.

Council of Science Editors:

Li Z. Vertex Models, Ising Models and Fisher Graphs. [Doctoral Dissertation]. Brown University; 2011. Available from: https://repository.library.brown.edu/studio/item/bdr:11314/

8. Loper, Jackson Hoy. Theory and Computation for Modern Probabilistic Models.

Degree: Department of Applied Mathematics, 2017, Brown University

 Modern probabilistic models involve computation and analysis in very high-dimensional spaces. Here we explore several of ways in which analysis of problems high dimensional spaces… (more)

Subjects/Keywords: Machine Learning

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APA (6th Edition):

Loper, J. H. (2017). Theory and Computation for Modern Probabilistic Models. (Thesis). Brown University. Retrieved from https://repository.library.brown.edu/studio/item/bdr:733424/

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

Chicago Manual of Style (16th Edition):

Loper, Jackson Hoy. “Theory and Computation for Modern Probabilistic Models.” 2017. Thesis, Brown University. Accessed November 28, 2020. https://repository.library.brown.edu/studio/item/bdr:733424/.

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

MLA Handbook (7th Edition):

Loper, Jackson Hoy. “Theory and Computation for Modern Probabilistic Models.” 2017. Web. 28 Nov 2020.

Vancouver:

Loper JH. Theory and Computation for Modern Probabilistic Models. [Internet] [Thesis]. Brown University; 2017. [cited 2020 Nov 28]. Available from: https://repository.library.brown.edu/studio/item/bdr:733424/.

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

Council of Science Editors:

Loper JH. Theory and Computation for Modern Probabilistic Models. [Thesis]. Brown University; 2017. Available from: https://repository.library.brown.edu/studio/item/bdr:733424/

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

9. Johnson, Dane Michael. Moderate Deviations and Subsolution-Based Importance Sampling for Recursive Stochastic Algorithms.

Degree: PhD, Applied Mathematics, 2015, Brown University

 We prove a moderate deviations principle for the continuous time linear interpolation of discrete time recursive stochastic processes, and then investigate importance sampling schemes based… (more)

Subjects/Keywords: Weak Convergence

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APA (6th Edition):

Johnson, D. M. (2015). Moderate Deviations and Subsolution-Based Importance Sampling for Recursive Stochastic Algorithms. (Doctoral Dissertation). Brown University. Retrieved from https://repository.library.brown.edu/studio/item/bdr:419359/

Chicago Manual of Style (16th Edition):

Johnson, Dane Michael. “Moderate Deviations and Subsolution-Based Importance Sampling for Recursive Stochastic Algorithms.” 2015. Doctoral Dissertation, Brown University. Accessed November 28, 2020. https://repository.library.brown.edu/studio/item/bdr:419359/.

MLA Handbook (7th Edition):

Johnson, Dane Michael. “Moderate Deviations and Subsolution-Based Importance Sampling for Recursive Stochastic Algorithms.” 2015. Web. 28 Nov 2020.

Vancouver:

Johnson DM. Moderate Deviations and Subsolution-Based Importance Sampling for Recursive Stochastic Algorithms. [Internet] [Doctoral dissertation]. Brown University; 2015. [cited 2020 Nov 28]. Available from: https://repository.library.brown.edu/studio/item/bdr:419359/.

Council of Science Editors:

Johnson DM. Moderate Deviations and Subsolution-Based Importance Sampling for Recursive Stochastic Algorithms. [Doctoral Dissertation]. Brown University; 2015. Available from: https://repository.library.brown.edu/studio/item/bdr:419359/

10. Wu, Wei. Large deviations and quasipotential for finite state mean field interacting particle systems.

Degree: PhD, Applied Mathematics, 2014, Brown University

 We study a general class of mean field interacting particle systems with a finite state space. Particles evolve as exchangeable jump Markov processes, where finite… (more)

Subjects/Keywords: interacting particle systems

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APA (6th Edition):

Wu, W. (2014). Large deviations and quasipotential for finite state mean field interacting particle systems. (Doctoral Dissertation). Brown University. Retrieved from https://repository.library.brown.edu/studio/item/bdr:386248/

Chicago Manual of Style (16th Edition):

Wu, Wei. “Large deviations and quasipotential for finite state mean field interacting particle systems.” 2014. Doctoral Dissertation, Brown University. Accessed November 28, 2020. https://repository.library.brown.edu/studio/item/bdr:386248/.

MLA Handbook (7th Edition):

Wu, Wei. “Large deviations and quasipotential for finite state mean field interacting particle systems.” 2014. Web. 28 Nov 2020.

Vancouver:

Wu W. Large deviations and quasipotential for finite state mean field interacting particle systems. [Internet] [Doctoral dissertation]. Brown University; 2014. [cited 2020 Nov 28]. Available from: https://repository.library.brown.edu/studio/item/bdr:386248/.

Council of Science Editors:

Wu W. Large deviations and quasipotential for finite state mean field interacting particle systems. [Doctoral Dissertation]. Brown University; 2014. Available from: https://repository.library.brown.edu/studio/item/bdr:386248/

11. Klobusicky, Joe J. Kinetic Limits of Piecewise Deterministic Markov Processes and Grain Boundary Coarsening.

Degree: PhD, Applied Mathematics, 2014, Brown University

 The subject of this thesis is the development of a stochastic process that can be interpreted as a model of grain coarsening, a central problem… (more)

Subjects/Keywords: grain coarsening

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APA (6th Edition):

Klobusicky, J. J. (2014). Kinetic Limits of Piecewise Deterministic Markov Processes and Grain Boundary Coarsening. (Doctoral Dissertation). Brown University. Retrieved from https://repository.library.brown.edu/studio/item/bdr:386230/

Chicago Manual of Style (16th Edition):

Klobusicky, Joe J. “Kinetic Limits of Piecewise Deterministic Markov Processes and Grain Boundary Coarsening.” 2014. Doctoral Dissertation, Brown University. Accessed November 28, 2020. https://repository.library.brown.edu/studio/item/bdr:386230/.

MLA Handbook (7th Edition):

Klobusicky, Joe J. “Kinetic Limits of Piecewise Deterministic Markov Processes and Grain Boundary Coarsening.” 2014. Web. 28 Nov 2020.

Vancouver:

Klobusicky JJ. Kinetic Limits of Piecewise Deterministic Markov Processes and Grain Boundary Coarsening. [Internet] [Doctoral dissertation]. Brown University; 2014. [cited 2020 Nov 28]. Available from: https://repository.library.brown.edu/studio/item/bdr:386230/.

Council of Science Editors:

Klobusicky JJ. Kinetic Limits of Piecewise Deterministic Markov Processes and Grain Boundary Coarsening. [Doctoral Dissertation]. Brown University; 2014. Available from: https://repository.library.brown.edu/studio/item/bdr:386230/

.