Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 2453 for “"probabilistic"”.
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Probabilistic data analysis with probabilistic programming
Probabilistic techniques are central to data analysis, but dierent approaches can be challenging to apply, combine, and compare. This thesis introduces composable generative population models (CGPMs), a computational abstraction that extends directed graphical models and can be used to describe and …
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Probabilistic Methods
The Probabilistic Method was primarily used in Combinatorics and pioneered by Erdös Pai, better known to Westerners as Paul Erdos in the 1950s. The probabilistic method is a powerful tool for solving many problems in discrete mathematics, combinatorics and also in graph .theory. It is also very …
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Reasoning with models of probabilistic knowledge over probabilistic knowledge
… we answer the question of how to model this probabilistic knowledge and reason about it efficiently. Modal logics enable representation of knowledge and belief by explicit reference to classical logical formulas in addition to references to those formulas’ truth values. Traditional modal …
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Natively probabilistic computation
I introduce a new set of natively probabilistic computing abstractions, including probabilistic generalizations of Boolean circuits, backtracking search and pure Lisp. I show how these tools let one compactly specify probabilistic generative models, generalize and parallelize widely used sampling …
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Practical probabilistic inference
The design and use of expert systems for medical diagnosis remains an attractive goal. One such system, the Quick Medical Reference, Decision Theoretic (QMR-DT), is based on a Bayesian network. This very large-scale network models the appearance and manifestation of disease and has approximately …
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Probabilistic Trans-Algorithmic Search
… such systems in an online manner, we propose a Probabilistic Trans-Algorithmic Search (PTAS) framework which leverages multiple optimization search algorithms in an iterative manner. PTAS applies a search algorithm to determine how to best distribute available experiment budget among multiple …
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Generalized Probabilistic Bowling Distributions
Have you ever wondered if you are better than the average bowler? If so, there are a variety of ways to compute the average score of a bowling game, including methods that account for a bowler’s skill level. In this thesis, we discuss several different ways to generate bowling scores randomly. For …
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Topics In Probabilistic Combinatorics
… of results in combinatorics utilizing the probabilistic method. Below is a brief description of the results highlighted in each chapter. Chapter 1 provides basic definitions, lemmas, and theorems from graph theory, asymptotic analysis, and probability which will be used throughout the …
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Probabilistic multiple kernel learning
… to address parts of that direction by proposing probabilistic data integration algorithms for multiclass decisions where an observation of interest is assigned to one of many categories based on a plurality of information channels.
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Topics in Probabilistic Combinatorics
This thesis consists of an introduction and eight chapters, each devoted to a different combinatorial problem. In Chapter 2, we study problems regarding reconstructing the entirety, or a large subset, of a point set $V$ embedded in either $\mathbb{R}$ or $\mathbb{R}^d$, where the only information …
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Probabilistic performance metric elicitation
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2022-11-11 without embargo terms
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Probabilistic semantics for vagueness
… inference. I thus propose a fundamentally probabilistic semantics for vagueness on which the meaning of a vague predicate is a likelihood function on the states it encodes, with these likelihoods being generated via reinforcement learning in a signaling game.
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Probabilistic Schwarzian Field Theory
… 4 we prove a large deviations principle for the probabilistic Schwarzian Theory at low temperatures. We demonstrate that the good rate function is equal to the action of the theory and find its minimisers. In addition, we define an analogue of the H\"{o}lder condition on the functional space …
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Probabilistic concurrent game semantics
This thesis presents a variety of models for probabilistic programming languages in the framework of concurrent games. Our starting point is the model of concurrent games with symmetry of Castellan, Clairambault and Winskel. We show that they form a symmetric monoidal closed bicategory, and that …
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Probabilistic vehicle routing problems
Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Civil Engineering, 1985.
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Probabilistic combinatorial optimization problems
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mathematics, 1988.
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Guiding Deep Probabilistic Models
Deep probabilistic models utilize deep neural networks to learn probability distributions in high-dimensional data spaces. Learning and inference in these models are complicated due to the difficulty of direct evaluation of the differences between the model distribution and the target. This thesis …
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Routing in probabilistic networks
… this thesis we develop an approach to routing in probabilistic networks in which these problems are addressed. The fundamental concept in our approach is that, for a given user with a set of routing options at a given node. we approximate the distributions of travel time for these options. Using …
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Conjoint probabilistic subband modeling
Thesis (Ph. D.)--Massachusetts Institute of Technology, Program in Media Arts & Sciences, 1997.
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