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Universal inference enables the construction of confidence intervals and tests without regularity conditions by splitting the data into two parts and appealing to Markov's inequality. Previous investigations have shown that the cost of this generality is a ...
This work studies the learning process over social networks under partial and random information sharing. In traditional social learning models, agents exchange full belief information with each other while trying to infer the true state of nature. We stud ...
Modern neuroscience research is generating increasingly large datasets, from recording thousands of neurons over long timescales to behavioral recordings of animals spanning weeks, months, or even years. Despite a great variety in recording setups and expe ...
EPFL2024
The archive of science is a place where scientific practices are sedimented in the form of drafts, protocols of rejected hypotheses and failed experiments, obsolete instruments, outdated visualizations and other residues. Today, just as science goes more a ...
EPFL2024
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This work addresses the problem of sharing partial information within social learning strategies. In social learning, agents solve a distributed multiple hypothesis testing problem by performing two operations at each instant: first, agents incorporate inf ...
An adaptive network consists of multiple communicating agents, equipped with sensing and learning abilities that allow them to extract meaningful information from measurements. The objective of the network is to solve a global inference problem in a decent ...
This work proposes a decentralized architecture, where individual agents aim at solving a classification problem while observing streaming features of different dimensions and arising from possibly different distributions. In the context of social learning ...
Future deep HI surveys will be essential for understanding the nature of galaxies and the content of the Universe. However, the large volume of these data will require distributed and automated processing techniques. We introduce LiSA, a set of python modu ...
ELSEVIER2022
This thesis addresses theoretical and practical aspects of identification and subsequent control of self-exciting point processes. The main contributions correspond to four separate scientific papers.In the first paper, we address the challenge of robust i ...
Can artificial agents benefit from human conventions? Human societies manage to successfully self-organize and resolve the tragedy of the commons in common-pool resources, in spite of the bleak prediction of non-cooperative game theory. On top of that, rea ...