439 citations · 2k across the 50 of their papers we have counts for
12 papers · 1 filter
A novel algorithm for online inexact string matching and its FPGA implementation
Alessandro Cinti, Filippo Maria Bianchi, Alessio Martino +1
Accelerating inexact string matching procedures is of utmost importance when dealing with practical applications where huge amount of data must be processed in real time, as usual…
Identifying user habits through data mining on call data records
Filippo Maria Bianchi, Antonello Rizzi, Alireza Sadeghian +1
In this paper we propose a framework for identifying patterns and regularities in the pseudo-anonymized Call Data Records (CDR) pertaining a generic subscriber of a mobile operator…
Classification of postoperative surgical site infections from blood measurements with missing data using recurrent neural networks
Andreas Storvik Strauman, Filippo Maria Bianchi, Karl Øyvind Mikalsen +3
Clinical measurements that can be represented as time series constitute an important fraction of the electronic health records and are often both uncertain and incomplete. Recurren…
Bidirectional deep-readout echo state networks
Filippo Maria Bianchi, Simone Scardapane, Sigurd Løkse +1
We propose a deep architecture for the classification of multivariate time series. By means of a recurrent and untrained reservoir we generate a vectorial representation that embed…
Learning compressed representations of blood samples time series with missing data
Filippo Maria Bianchi, Karl Øyvind Mikalsen, Robert Jenssen
Clinical measurements collected over time are naturally represented as multivariate time series (MTS), which often contain missing data. An autoencoder can learn low dimensional ve…
An overview and comparative analysis of Recurrent Neural Networks for Short Term Load Forecasting
Filippo Maria Bianchi, Enrico Maiorino, Michael C. Kampffmeyer +2
The key component in forecasting demand and consumption of resources in a supply network is an accurate prediction of real-valued time series. Indeed, both service interruptions an…
Time Series Cluster Kernel for Learning Similarities between Multivariate Time Series with Missing Data
Karl Øyvind Mikalsen, Filippo Maria Bianchi, Cristina Soguero-Ruiz +1
Similarity-based approaches represent a promising direction for time series analysis. However, many such methods rely on parameter tuning, and some have shortcomings if the time se…
Local Short Term Electricity Load Forecasting: Automatic Approaches
The-Hien Dang-Ha, Filippo Maria Bianchi, Roland Olsson
Short-Term Load Forecasting (STLF) is a fundamental component in the efficient management of power systems, which has been studied intensively over the past 50 years. The emerging…
Spectral Clustering using PCKID - A Probabilistic Cluster Kernel for Incomplete Data
Sigurd Løkse, Filippo Maria Bianchi, Arnt-Børre Salberg +1
In this paper, we propose PCKID, a novel, robust, kernel function for spectral clustering, specifically designed to handle incomplete data. By combining posterior distributions of…
A clustering approach to heterogeneous change detection
Luigi Tommaso Luppino, Stian Normann Anfinsen, Gabriele Moser +4
Change detection in heterogeneous multitemporal satellite images is a challenging and still not much studied topic in remote sensing and earth observation. This paper focuses on co…
Deep Kernelized Autoencoders
Michael Kampffmeyer, Sigurd Løkse, Filippo Maria Bianchi +2
In this paper we introduce the deep kernelized autoencoder, a neural network model that allows an explicit approximation of (i) the mapping from an input space to an arbitrary, use…
Temporal Overdrive Recurrent Neural Network
Filippo Maria Bianchi, Michael Kampffmeyer, Enrico Maiorino +1
In this work we present a novel recurrent neural network architecture designed to model systems characterized by multiple characteristic timescales in their dynamics. The proposed…