Publications related to Conditional probability

Predicting involuntary hospitalization in psychiatry: A machine learning investigation

Background Coercion in psychiatry is a controversial issue. Identifying its predictors and their interaction using traditional statistical methods is difficult, given the large number of variables involved. The purpose of this study was to use machine-lear ...

CAMBRIDGE UNIV PRESS2021

A General Framework for Optimal Data-Driven Optimization

Daniel Kuhn, Tobias Sutter

We propose a statistically optimal approach to construct data-driven decisions for stochastic optimization problems. Fundamentally, a data-driven decision is simply a function that maps the available training data to a feasible action. It can always be exp ...

2021

Generalization Error Bounds Via Rényi-, f-Divergences and Maximal Leakage

Michael Christoph Gastpar, Amedeo Roberto Esposito, Ibrahim Issa

In this work, the probability of an event under some joint distribution is bounded by measuring it with the product of the marginals instead (which is typically easier to analyze) together with a measure of the dependence between the two random variables. ...

2021

Learning in Volatile Environments With the Bayes Factor Surprise

Wulfram Gerstner, Johanni Michael Brea, Alireza Modirshanechi, Vasiliki Liakoni

Surprise-based learning allows agents to rapidly adapt to nonstationary stochastic environments characterized by sudden changes. We show that exact Bayesian inference in a hierarchical model gives rise to a surprise-modulated trade-off between forgetting o ...

MIT PRESS2021

Efficient Bootstrapping for Approximate Homomorphic Encryption with Non-sparse Keys

Jean-Pierre Hubaux, Juan Ramón Troncoso-Pastoriza, Jean-Philippe Léonard Bossuat, Christian Vincent Mouchet

We present a bootstrapping procedure for the full-RNS variant of the approximate homomorphic-encryption scheme of Cheon et al., CKKS (Asiacrypt 17, SAC 18). Compared to the previously proposed procedures (Eurocrypt 18 & 19, CT-RSA 20), our bootstrapping pr ...

SPRINGER INTERNATIONAL PUBLISHING AG2021

A decomposition of multicorrelation sequences for commuting transformations along primes

Florian Karl Richter

A decomposition of multicorrelation sequences for commuting transformations along primes, Discrete Analysis 2021:4, 27 pp. Szemerédi's theorem asserts that for every positive integer

k

and every

\delta>0

there exists

n

such that every subset of ${1, ...

2021

Normalized Gaussian path integrals

Giulio Corazza

Path integrals play a crucial role in describing the dynamics of physical systems subject to classical or quantum noise. In fact, when correctly normalized, they express the probability of transition between two states of the system. In this work, we show ...

AMER PHYSICAL SOC2020

Robust Generalization via $\alpha$-Mutual Information

Michael Christoph Gastpar, Amedeo Roberto Esposito, Ibrahim Issa

The aim of this work is to provide bounds connecting two probability measures of the same event using Rényi

\alpha

-Divergences and Sibson’s

\alpha

-Mutual Information, a generalization of respectively the Kullback-Leibler Divergence and Shannon’s Mutual ...

ETHZ2020

Tighter thermodynamic bound on the speed limit in systems with unidirectional transitions

Daniel Maria Busiello, Deepak Gupta

We consider a general discrete state-space system with both unidirectional and bidirectional links. In contrast to bidirectional links, there is no reverse transition along the unidirectional links Herein, we first compute the statistical length and the th ...

2020

Statistical Fatigue Investigation and Failure Prediction of a Healable Composite System

Véronique Michaud, Amaël Maximilien Cohades

Fiber reinforced polymers are massively used as an alternative to metals in structural applications. The brittle nature of their matrix, however, makes them more susceptible to crack formation and propagation resulting in costly repair operations and incre ...

2020

Conditional probability

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Predicting involuntary hospitalization in psychiatry: A machine learning investigation

A General Framework for Optimal Data-Driven Optimization

Generalization Error Bounds Via Rényi-, f-Divergences and Maximal Leakage

Learning in Volatile Environments With the Bayes Factor Surprise

Efficient Bootstrapping for Approximate Homomorphic Encryption with Non-sparse Keys

A decomposition of multicorrelation sequences for commuting transformations along primes

Normalized Gaussian path integrals

Robust Generalization via $\alpha$-Mutual Information

Tighter thermodynamic bound on the speed limit in systems with unidirectional transitions

Statistical Fatigue Investigation and Failure Prediction of a Healable Composite System

A General Framework for Optimal Data-Driven Optimization

A decomposition of multicorrelation sequences for commuting transformations along primes

Normalized Gaussian path integrals

Robust Generalization via $\alpha$-Mutual Information

Tighter thermodynamic bound on the speed limit in systems with unidirectional transitions

Predicting involuntary hospitalization in psychiatry: A machine learning investigation

Generalization Error Bounds Via Rényi-, f-Divergences and Maximal Leakage

Learning in Volatile Environments With the Bayes Factor Surprise

Efficient Bootstrapping for Approximate Homomorphic Encryption with Non-sparse Keys

Statistical Fatigue Investigation and Failure Prediction of a Healable Composite System