F. Aiolli

发表

Preference Learning: Problems and Applications in Ai Preference Learning: Problems and Applications in Ai (pl-12) Contents a Preliminary Study on a Recommender System for the Million Songs Dataset Using and Learning Gai-decompositions for Representing Ordinal Rankings Alleviating Cold-user Start Pro

Marc Schoenauer, Johannes Fürnkranz, E. Hüllermeier, 2012 .

2 GPLM : A General Model for Supervised Learning 2 . 1 The Learning Domain

A. Sperduti, F. Aiolli, 2019 .

Supervised Learning as Preference Optimization : A General Framework and its Applications

A. Sperduti, F. Aiolli, 2008 .

Novel Applications for VAE-based Anomaly Detection Systems

F. Aiolli, L. Bergamin, Tommaso Carraro, 2022, 2022 International Joint Conference on Neural Networks (IJCNN).

SPI: A System for Paleographic Inspections

Alessandro Sperduti, Maria Simi, Antonina Starita, 1999 .

Advances in artificial neural networks, machine learning and computational intelligence

Luca Oneto, Michael Biehl, Fabio Aiolli, 2011, Neurocomputing.

Deliverable 1 . 6 Data fusion guidelines

A. Sperduti, S. Kollet, C. Montzka, 2018 .

Deliverable 1 . 3 Modelling and processing services and tools

A. Sperduti, S. Kollet, C. Montzka, 2018 .

Special issue: Advances in artificial neural networks, machine learning and computational intelligenceSelected papers from the 23rd European Symposium on Artificial Neural Networks (ESANN 2015)

Mikhail F. Kanevski, Romain Hérault, Fabio Aiolli, 2016, Neurocomputing.

Advances in artificial neural networks, machine learning and computational intelligence

Alessandro Sperduti, Luca Oneto, Kerstin Bunte, 2011, Neurocomputing.

Exploring the structure of BERT through Kernel Learning

Alessandro Moschitti, A. Lavelli, Ivano Lauriola, 2021, 2021 International Joint Conference on Neural Networks (IJCNN).

Social Support and Help-Seeking Among Suicide Bereaved: A Study With Italian Survivors

D. Leo, O. Gaggi, S. Cipolletta, 2021, Omega.

Large Margin Multiclass Learning: Models and Algorithms

Fabio Aiolli, F. Aiolli, 2004 .

Improving biomarker list stability by integration of biological knowledge in the learning process

Giovanni Da San Martino, Fabio Aiolli, Barbara Di Camillo, 2012, BMC Bioinformatics.

Scuba: scalable kernel-based gene prioritization

Giorgio Valle, Alessandro Sperduti, Fabio Aiolli, 2018, BMC Bioinformatics.

Radical scavenging activity of natural antioxidants and drugs: Development of a combined machine learning and quantum chemistry protocol.

Mirko Polato, Fabio Aiolli, Laura Orian, 2020, The Journal of chemical physics.

Self-Organizing Maps for Structured Domains: Theory, Models, and Learning of Kernels

Markus Hagenbuchner, Alessandro Sperduti, Giovanni Da San Martino, 2009, Innovations in Neural Information Paradigms and Applications.

Efficient Kernel-based Learning for Trees

Alessandro Sperduti, Alessandro Moschitti, Giovanni Da San Martino, 2007, 2007 IEEE Symposium on Computational Intelligence and Data Mining.

Fast On-line Kernel Learning for Trees

Alessandro Sperduti, Alessandro Moschitti, Giovanni Da San Martino, 2006, Sixth International Conference on Data Mining (ICDM'06).

An introduction to Deep Learning in Natural Language Processing: Models, techniques, and tools

Alberto Lavelli, Ivano Lauriola, Fabio Aiolli, 2021, Neurocomputing.

Boolean kernels for rule based interpretation of support vector machines

Mirko Polato, Fabio Aiolli, F. Aiolli, 2019, Neurocomputing.

Transfer Learning by Kernel Meta-Learning

Fabio Aiolli, F. Aiolli, 2011, ICML Unsupervised and Transfer Learning.

Mind your wallet's privacy: identifying Bitcoin wallet apps and user's actions through network traffic analysis

Mauro Conti, Mirko Polato, Fabio Aiolli, 2019, SAC.

Recency Aware Collaborative Filtering for Next Basket Recommendation

Mirko Polato, Fabio Aiolli, Guglielmo Faggioli, 2020, UMAP.

Efficient top-n recommendation for very large scale binary rated datasets

Fabio Aiolli, F. Aiolli, 2013, RecSys.

A systematic review of value-aware recommender systems

Alvise De Biasio, F. Aiolli, Nicoló Navarin, 2023, Expert Syst. Appl..

Conditioned Variational Autoencoder for top-N item recommendation pdf

Mirko Polato, Fabio Aiolli, Tommaso Carraro, 2020, ICANN.

Route kernels for trees

Alessandro Sperduti, Giovanni Da San Martino, Fabio Aiolli, 2009, ICML '09.

The minimum effort maximum output principle applied to Multiple Kernel Learning

Mirko Polato, Ivano Lauriola, Fabio Aiolli, 2018, ESANN.

Radius-Margin Ratio Optimization for Dot-Product Boolean Kernel Learning

Mirko Polato, Ivano Lauriola, Fabio Aiolli, 2017, ICANN.

Learning deep kernels in the space of dot product polynomials

Fabio Aiolli, Michele Donini, Michele Donini, 2017, Machine Learning.

Learning deep kernels in the space of monotone conjunctive polynomials

Mirko Polato, Ivano Lauriola, Fabio Aiolli, 2020, Pattern Recognit. Lett..

Multi-prototype Support Vector Machine

Alessandro Sperduti, Fabio Aiolli, A. Sperduti, 2003, IJCAI.

Propositional Kernels

Mirko Polato, Fabio Aiolli, F. Aiolli, 2021, Entropy.

A Novel Boolean Kernels Family for Categorical Data †

Mirko Polato, Ivano Lauriola, Fabio Aiolli, 2018, Entropy.

A preliminary study on a recommender system for the job recommendation challenge

Mirko Polato, Fabio Aiolli, F. Aiolli, 2016, RecSys Challenge '16.

Learning adaptive representations for entity recognition in the biomedical domain

Fabio Rinaldi, Alberto Lavelli, Ivano Lauriola, 2021, Journal of Biomedical Semantics.

ClimbTheWorld: real-time stairstep counting to increase physical activity

Ombretta Gaggi, Fabio Aiolli, Michele Donini, 2014, MobiQuitous.

DecOp: A Multilingual and Multi-domain Corpus For Detecting Deception In Typed Text

Carlo Strapparava, Giuseppe Sartori, Ivano Lauriola, 2020, LREC.

Learning Preferences for Multiclass Problems

Alessandro Sperduti, Fabio Aiolli, A. Sperduti, 2004, NIPS.

Stairstep recognition and counting in a serious Game for increasing users’ physical activity

Ombretta Gaggi, Fabio Aiolli, Michele Donini, 2016, Personal and Ubiquitous Computing.

Boolean kernels for interpretable kernel machines

Mirko Polato, Fabio Aiolli, F. Aiolli, 2018, ESANN.

Learning With Kernels: A Local Rademacher Complexity-Based Analysis With Application to Graph Kernels

Alessandro Sperduti, Davide Anguita, Luca Oneto, 2018, IEEE Transactions on Neural Networks and Learning Systems.

Measuring the expressivity of graph kernels through Statistical Learning Theory

Alessandro Sperduti, Davide Anguita, Luca Oneto, 2017, Neurocomputing.

Multiple Graph-Kernel Learning

Alessandro Sperduti, Fabio Aiolli, Nicolò Navarin, 2015, 2015 IEEE Symposium Series on Computational Intelligence.

EasyMKL: a scalable multiple kernel learning algorithm

Fabio Aiolli, Michele Donini, Michele Donini, 2015, Neurocomputing.

Measuring the Expressivity of Graph Kernels through the Rademacher Complexity

Alessandro Sperduti, Davide Anguita, Luca Oneto, 2016, ESANN.

Advances in Learning with Kernels: Theory and Practice in a World of growing Constraints

Davide Anguita, Luca Oneto, Fabio Aiolli, 2016, ESANN.

A Kernel Method for the Optimization of the Margin Distribution

Alessandro Sperduti, Giovanni Da San Martino, Fabio Aiolli, 2008, ICANN.

MKLpy: a python-based framework for Multiple Kernel Learning pdf

Ivano Lauriola, Fabio Aiolli, Ivano Lauriola, 2020, ArXiv.

Enhancing deep neural networks via multiple kernel learning

Claudio Gallicchio, Ivano Lauriola, Fabio Aiolli, 2020, Pattern Recognit..

A Preference Optimization Based Unifying Framework for Supervised Learning Problems

Alessandro Sperduti, Fabio Aiolli, A. Sperduti, 2010, Preference Learning.

Bayes Point Rule Set Learning

F. Aiolli, Tommaso Carraro, Mirko Polato, 2022, ESANN.

An Efficient Topological Distance-Based Tree Kernel

Alessandro Sperduti, Giovanni Da San Martino, Fabio Aiolli, 2015, IEEE Transactions on Neural Networks and Learning Systems.

Enhancing Artificial Intelligence in Games by Learning the Opponent's Playing Style

Claudio E. Palazzi, Fabio Aiolli, C. Palazzi, 2008, ECS.

Multiclass Classification with Multi-Prototype Support Vector Machines

Alessandro Sperduti, Fabio Aiolli, A. Sperduti, 2005, J. Mach. Learn. Res..

A Business Process Metric Based on the Alpha Algorithm Relations

Alessandro Sperduti, Fabio Aiolli, Andrea Burattin, 2011, Business Process Management Workshops.

Language processing in the era of deep learning

A. Lavelli, Ivano Lauriola, F. Aiolli, 2020, ESANN.

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

Mirko Polato, Fabio Aiolli, F. Aiolli, 2016, Neurocomputing.

Efficient Online Learning for Mapping Kernels on Linguistic Structures

Alessandro Sperduti, Alessandro Moschitti, Giovanni Da San Martino, 2019, AAAI.

Evaluation of Tag Clusterings for User Profiling in Movie Recommendation

Mirko Polato, Ivano Lauriola, Fabio Aiolli, 2019, ICANN.

Psychiatric Disorders Classification with 3D Convolutional Neural Networks

Giuseppe Sartori, Ivano Lauriola, Fabio Aiolli, 2019, INNSBDDL.

Learning Nonsparse Kernels by Self-Organizing Maps for Structured Data

Markus Hagenbuchner, Alessandro Sperduti, Giovanni Da San Martino, 2009, IEEE Transactions on Neural Networks.

Mirko Polato, Fabio Aiolli, Guglielmo Faggioli, 2018, RecSys Challenge.

Playing the Large Margin Preference Game

Mirko Polato, Ivano Lauriola, Fabio Aiolli, 2019, ICANN.

Tag-Based User Profiling: A Game Theoretic Approach

Mirko Polato, Fabio Aiolli, Guglielmo Faggioli, 2019, UMAP.

Monotone Deep Spectrum Kernels

Ivano Lauriola, Fabio Aiolli, Ivano Lauriola, 2020, ICANN.

A Look Inside the Black-Box: Towards the Interpretability of Conditioned Variational Autoencoder for Collaborative Filtering

Mirko Polato, Fabio Aiolli, Tommaso Carraro, 2020, UMAP.