
Generating Negations of Probability Distributions
Recently it was introduced a negation of a probability distribution. The...
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Improved Chebyshev inequality: new probability bounds with known supremum of PDF
In this paper, we derive new probability bounds for Chebyshev's inequali...
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On Finite Exchangeability and Conditional Independence
We study the independence structure of finitely exchangeable distributio...
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A short note on learning discrete distributions
The goal of this short note is to provide simple proofs for the "folklor...
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On Learning Discrete Graphical Models Using Greedy Methods
In this paper, we address the problem of learning the structure of a pai...
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Distribution Regression Network
We introduce our Distribution Regression Network (DRN) which performs re...
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On the Trackability of Stochastic Processes
We consider the problem of estimating the state of a discrete stochastic...
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Factorization of Discrete Probability Distributions
We formulate necessary and sufficient conditions for an arbitrary discrete probability distribution to factor according to an undirected graphical model, or a loglinear model, or other more general exponential models. This result generalizes the well known HammersleyClifford Theorem.
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