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 40 for “"Probability measures."”.
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Convergence of empirical probability measures
Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Mathematics, 1982.
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Exploring Probability Measures with Markov Processes
… the state of the system as being drawn from a probability measure, which is usually given algebraically, i.e. as a formula. While this representation can be useful for deriving certain characteristics of the system, it is by now well-appreciated that many questions about stochastic systems are …
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Diversity-inducing probability measures for machine learning
… is to sample according to Diversity-Inducing Probability Measures (DIPMs) that assign higher probabilities to more diverse subsets. DIPMs underlie several recent breakthroughs in mathematics and theoretical computer science, but their power has not yet been explored for machine learning. In …
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Analysis Of Sequential Barycenter Random Probability Measures via Discrete Constructions
… a constructive method for generating random probability measures with a prescribed mean or distribution on the mean. The method involves sequentially generating an array of barycenters that uniquely defines a probability measure. This work analyzes statistical properties of the measures …
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Riemannian Metric Learning via Optimal Transport
… tensor from cross-sectional samples of evolving probability measures on a common Riemannian manifold. We neurally parametrize the metric as a spatially-varying matrix field and efficiently optimize our model's objective using backpropagation. Using this learned metric, we can nonlinearly …
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Convergence of Gibbs measures and the behavior of shrinking tubular neighborhoods of fractals and algebraic sets
… of a Gibbs measure, which is a certain probability measure on Euclidean space. In this paper we examine a sequence of Gibbs measures characterized by the distance function. In Chapter 2 we conclude that the sequence of measures converge to a Hausdorff probability measure equally …
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Trimatė ribinė teorema periodinėms dzeta funkcijoms /
… theorem in the sense of weak convergence of probability measures for the periodic zeta-functions. The result formulated by theorem.
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Tikimybinių matų charakteringosios transformacijos /
… the weak convergence in the sense of X for the probability measures fallows.
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Probabilistic concurrent game semantics
… by linear logic. Then, we enrich this with probability, relying heavily on Winskel's model of probabilistic concurrent strategies. We see that the bicategorical structure is not perturbed by the addition of probability. We apply this model to two probabilistic languages: a probabilistic …
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d-bar continuity beyond subshifts of finite type
… in the $\overline{d}$-metric on the space of measures and the metric coming from the Hölder norm on the space of potentials. The concept of $\overline{d}$-distance on the space of invariant measures on a shift space was introduced by Ornstein to study the isomorphism problem for Bernoulli …
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Vietoris–Rips metric thickenings and Wasserstein spaces
… as a subset of the Wasserstein space of probability measures on X. Such spaces are called simplicial metric thickenings, and a prominent example is the Vietoris–Rips metric thickening. In this work we study these spaces from three perspectives: metric geometry, optimal transport, and …
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Speaker Identification Based On Discriminative Vector Quantization And Data Fusion
… DVQSI (ADVQSI) methods. The difference of the probability distributions of the speech feature vector sets from various speakers (or speaker groups) is called the interspeaker variation between speakers (or speaker groups). The interspeaker variation is the measure of template differences …
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Feynman-Kac Numerical Techniques for Stochastic Optimal Control
… By the repeated use of the Girsanov change of probability measures, it is demonstrated how a McKean-Markov branched sampling method can be utilized for the forward integration pass, as long as the controlled drift terms are appropriately compensated in the backward integration pass. …
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A new approach to fitting linear models in high dimensional spaces
… minimum distance approach, including probability measures and nonnegative measures, is proposed, and strongly consistent estimators are produced. Of all minimum distance methods for estimating a mixing distribution, only the nonnegative-measure-based one solves the minority cluster …
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A measure for the number of commuting subgroups in compact groups
… thesis is devoted to the construction of a probability measure which counts the pairs of closed commuting subgroups in infinite groups. This measure turns out to be an extension of what was known in the finite case as subgroup commutativity degree and opens a new approach of study for the …
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Point processes of representation theoretic origin
… functions of the 4-parameter family of BC type Z-measures. The result is given explicitly in terms of Gauss's hypergeometric function. The BC type Z-measures are point processes on the punctured positive real line. They arise as interpolations of the spectral measures of a distinguished family of …
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Numerical methods for problems arising in risk management and insurance
… and based on the theory of weak convergence of probability measures, the convergence of the approximating sequences is obtained. In fact, under very broad conditions, we prove that the sequences of approximating Markov chain, the cost functions, and the value functions all converge to that of …
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Modelling financial time series using discrete and continuous paradigms
… and hence on the existence of risk-neutral probability measures, for which the discounted asset price process is a martingale. Having modelled the stock price evolution in discrete time, we shall next move on to continuous-time models, namely the Diffusion process, which is described by a …
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Quantization Dimension for Probability Definitions
… refers to the process of estimating a given probability by a discrete probability supported on a finite set. The quantization dimension Dr of a probability is related to the asymptotic rate at which the expected distance (raised to the rth power) to the support of the quantized version of the …
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Qualitative and quantitative convergence results for randomised integration methods
… is consistent w.r.t. convergence in mean and probability for any integrable function. Under slightly stronger integrability conditions we show that one also has almost sure convergence for median modified methods. We demonstrate the applicability of our theoretical results by considering …
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