Publications associées à Bayesian programming

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

Quantifying Interdependent Privacy Risks with Location Data

Jean-Pierre Hubaux, Mathias Jacques Jean-Marc Humbert, Kévin Clément Huguenin, Reza Shokri, Alexandra-Mihaela Olteanu

Co-location information about users is increasingly available online. For instance, mobile users more and more frequently report their co-locations with other users in the messages and in the pictures they post on social networking websites by tagging the ...

Ieee Computer Soc2017

An Adaptive Algorithm for Efficient Message Diffusion in Unreliable Environments

Rodrigo Malta Schmidt, Benoît Garbinato, Fernando Pedone

In this paper, we propose a novel approach for solving the reliable broadcast problem in a probabilistic model, i.e., where links lose messages and where processes crash and recover probabilistically. Our approach consists in first defining the optimality ...

2004

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Bayesian programming

Learning in Volatile Environments With the Bayes Factor Surprise

Quantifying Interdependent Privacy Risks with Location Data

Efficient Peer-to-Peer Belief Propagation

An Adaptive Algorithm for Efficient Message Diffusion in Unreliable Environments

Graph Chatbot

Chattez avec Graph Search

Learning in Volatile Environments With the Bayes Factor Surprise

An Adaptive Algorithm for Efficient Message Diffusion in Unreliable Environments

Quantifying Interdependent Privacy Risks with Location Data

Efficient Peer-to-Peer Belief Propagation