Search Results for author: Luca Corinzia

Found 6 papers, 1 papers with code

IFedAvg: Interpretable Data-Interoperability for Federated Learning

1 code implementation14 Jul 2021 David Roschewitz, Mary-Anne Hartley, Luca Corinzia, Martin Jaggi

Thus, enabling the detection of outlier datasets in the federation and also learning the compensation for local data distribution shifts without sharing any original data.

Federated Learning

On maximum-likelihood estimation in the all-or-nothing regime

no code implementations25 Jan 2021 Luca Corinzia, Paolo Penna, Wojciech Szpankowski, Joachim M. Buhmann

The result follows from two main technical points: (i) the connection established between the MLE and the MMSE, using the first and second-moment methods in the constrained signal space, (ii) a recovery regime for the MMSE stricter than the simple error vanishing characterization given in the standard AoN, that is here proved as a general result.

Statistical and computational thresholds for the planted $k$-densest sub-hypergraph problem

no code implementations23 Nov 2020 Luca Corinzia, Paolo Penna, Wojciech Szpankowski, Joachim M. Buhmann

In this work, we consider the problem of recovery a planted $k$-densest sub-hypergraph on $d$-uniform hypergraphs.

Community Detection

Neural collaborative filtering for unsupervised mitral valve segmentation in echocardiography

no code implementations13 Aug 2020 Luca Corinzia, Fabian Laumer, Alessandro Candreva, Maurizio Taramasso, Francesco Maisano, Joachim M. Buhmann

The segmentation of the mitral valve annulus and leaflets specifies a crucial first step to establish a machine learning pipeline that can support physicians in performing multiple tasks, e. g.\ diagnosis of mitral valve diseases, surgical planning, and intraoperative procedures.

Collaborative Filtering Segmentation

Variational Federated Multi-Task Learning

no code implementations14 Jun 2019 Luca Corinzia, Ami Beuret, Joachim M. Buhmann

Despite federated multi-task learning being shown to be an effective paradigm for real-world datasets, it has been applied only on convex models.

Federated Learning Multi-Task Learning +1

A Spectral Method for Activity Shaping in Continuous-Time Information Cascades

no code implementations15 Sep 2017 Kevin Scaman, Argyris Kalogeratos, Luca Corinzia, Nicolas Vayatis

Information Cascades Model captures dynamical properties of user activity in a social network.

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