Publications associées à Metropolis-Hastings sampling of paths

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Sublinear Bounds on the Distinguishing Advantage for Multiple Samples

Serge Vaudenay

The maximal achievable advantage of a (computationally unbounded) distinguisher to determine whether a source

Z

is distributed according to distribution

P_0

P_1

, when given access to one sample of

Z

, is characterized by the statistical distance ...

Springer, Cham2020

Metropolis-Hastings sampling of paths

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Printed Iontophoretic‐Integrated Wearable Microfluidic Sweat‐Sensing Patch for On‐Demand Point‐Of‐Care Sweat Analysis

A statistical approach for the automatic identification of the start of the chain of events leading to the disruptions at JET

Collaborative Sampling in Generative Adversarial Networks

Multi-armed Bandits in Action

From Data to Decisions: Distributionally Robust Optimization is Optimal

Sublinear Bounds on the Distinguishing Advantage for Multiple Samples

Variational Inference with Mixture Model Approximation for Applications in Robotics

Slope-Space Integrals for Specular Next Event Estimation

Retroactive Packet Sampling for Traffic Receipts

Approximation of Non-decaying Signals from Shift-Invariant Subspaces

Multi-armed Bandits in Action

Approximation of Non-decaying Signals from Shift-Invariant Subspaces

Sublinear Bounds on the Distinguishing Advantage for Multiple Samples

Variational Inference with Mixture Model Approximation for Applications in Robotics

Slope-Space Integrals for Specular Next Event Estimation

A statistical approach for the automatic identification of the start of the chain of events leading to the disruptions at JET

Collaborative Sampling in Generative Adversarial Networks

From Data to Decisions: Distributionally Robust Optimization is Optimal

Printed Iontophoretic‐Integrated Wearable Microfluidic Sweat‐Sensing Patch for On‐Demand Point‐Of‐Care Sweat Analysis

Retroactive Packet Sampling for Traffic Receipts