Mirko Polato | DeepAI

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∙ 02/15/2023

Experimenting with Emerging ARM and RISC-V Systems for Decentralised Machine Learning

Decentralised Machine Learning (DML) enables collaborative machine learn...

0 Gianluca Mittone, et al. ∙

∙ 04/26/2022

Novel Applications for VAE-based Anomaly Detection Systems

The recent rise in deep learning technologies fueled innovation and boos...

0 Luca Bergamin, et al. ∙

∙ 04/11/2022

Bayes Point Rule Set Learning

Interpretability is having an increasingly important role in the design ...

0 Fabio Aiolli, et al. ∙

∙ 04/16/2020

Conditioned Variational Autoencoder for top-N item recommendation

In this paper, we propose a Conditioned Variational Autoencoder to impro...

0 Mirko Polato, et al. ∙

∙ 12/19/2018

Interpretable preference learning: a game theoretic framework for large margin on-line feature and rule learning

A large body of research is currently investigating on the connection be...

0 Mirko Polato, et al. ∙

∙ 11/10/2017

LSTM Networks for Data-Aware Remaining Time Prediction of Business Process Instances

Predicting the completion time of business process instances would be a ...

0 Nicolò Navarin, et al. ∙

∙ 12/21/2016

Boolean kernels for collaborative filtering in top-N item recommendation

In many personalized recommendation problems available data consists onl...

0 Mirko Polato, et al. ∙

∙ 12/17/2016

Exploiting sparsity to build efficient kernel based collaborative filtering for top-N item recommendation

The increasing availability of implicit feedback datasets has raised the...

0 Mirko Polato, et al. ∙

∙ 02/24/2016

Time and Activity Sequence Prediction of Business Process Instances

The ability to know in advance the trend of running process instances, w...

0 Mirko Polato, et al. ∙

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