117 citations · 131 across the 7 of their papers we have counts for
9 papers
Breeding Programs Optimization with Reinforcement Learning
Omar G. Younis, Luca Corinzia, Ioannis N. Athanasiadis +3
Crop breeding is crucial in improving agricultural productivity while potentially decreasing land usage, greenhouse gas emissions, and water consumption. However, breeding programs…
IFedAvg: Interpretable Data-Interoperability for Federated Learning
David Roschewitz, Mary-Anne Hartley, Luca Corinzia +1
Recently, the ever-growing demand for privacy-oriented machine learning has motivated researchers to develop federated and decentralized learning techniques, allowing individual cl…
On maximum-likelihood estimation in the all-or-nothing regime
Luca Corinzia, Paolo Penna, Wojciech Szpankowski +1
We study the problem of estimating a rank-1 additive deformation of a Gaussian tensor according to the \emph{maximum-likelihood estimator} (MLE). The analysis is carried out in the…
Statistical and computational thresholds for the planted -densest sub-hypergraph problem
Luca Corinzia, Paolo Penna, Wojciech Szpankowski +1
In this work, we consider the problem of recovery a planted -densest sub-hypergraph on -uniform hypergraphs. This fundamental problem appears in different contexts, e.g., com…
Neural collaborative filtering for unsupervised mitral valve segmentation in echocardiography
Luca Corinzia, Fabian Laumer, Alessandro Candreva +3
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…
The Next 700 Policy Miners: A Universal Method for Building Policy Miners
Carlos Cotrini, Luca Corinzia, Thilo Weghorn +1
A myriad of access control policy languages have been and continue to be proposed. The design of policy miners for each such language is a challenging task that has required specia…
Variational Federated Multi-Task Learning
Luca Corinzia, Ami Beuret, Joachim M. Buhmann
In federated learning, a central server coordinates the training of a single model on a massively distributed network of devices. This setting can be naturally extended to a multi-…
Exact Recovery for a Family of Community-Detection Generative Models
Luca Corinzia, Paolo Penna, Luca Mondada +1
Generative models for networks with communities have been studied extensively for being a fertile ground to establish information-theoretic and computational thresholds. In this pa…
A Spectral Method for Activity Shaping in Continuous-Time Information Cascades
Kevin Scaman, Argyris Kalogeratos, Luca Corinzia +1
Information Cascades Model captures dynamical properties of user activity in a social network. In this work, we develop a novel framework for activity shaping under the Continuous-…