Ivano Lauriola

发表

Classification of Categorical Data in the Feature Space of Monotone DNFs

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

Context-based Transformer Models for Answer Sentence Selection pdf

Alessandro Moschitti, Ivano Lauriola, Alessandro Moschitti, 2020, ArXiv.

Exploring the feature space of character-level embeddings

Fabio Rinaldi, Alberto Lavelli, Ivano Lauriola, 2020, ESANN.

Language processing in the era of deep learning

Alberto Lavelli, Ivano Lauriola, Fabio Aiolli, 2020, ESANN.

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

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

On the Impact of Early Stopping in Multiple Kernel Learning

Ivano Lauriola, 2020 .

Monotone Deep Spectrum Kernels

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

Learning dot-product polynomials for multiclass problems

Ivano Lauriola, Fabio Aiolli, Michele Donini, 2017, ESANN.

A Heuristic for Multi-attribute Vehicle Routing Problems in Express Freight Transportation

Ivano Lauriola, Luigi De Giovanni, Nicola Gastaldon, 2017 .

Do people believe in Artificial Intelligence?: A cross-topic multicultural study

Agnieszka Kolasinska, Giacomo Quadrio, Ivano Lauriola, 2019, GOODTECHS.

Enhancing deep neural networks via multiple kernel learning

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

Playing the Large Margin Preference Game

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

Learning Preferences for Large Scale Multi-label Problems

Fabio Rinaldi, Alberto Lavelli, Mirko Polato, 2018, ICANN.

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

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

Evaluation of Tag Clusterings for User Profiling in Movie Recommendation

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

Fast hyperparameter selection for graph kernels via subsampling and multiple kernel learning

Fabrizio Costa, Ivano Lauriola, Fabio Aiolli, 2017, ESANN.

Psychiatric Disorders Classification with 3D Convolutional Neural Networks

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

A Novel Boolean Kernels Family for Categorical Data †

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

A Preference-Learning Framework for Modeling Relational Data

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

The minimum effort maximum output principle applied to Multiple Kernel Learning

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

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

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

Learning deep kernels in the space of monotone conjunctive polynomials

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

Learning Representations for Biomedical Named Entity Recognition

Fabio Rinaldi, Alberto Lavelli, Ivano Lauriola, 2018 .

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

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

Exploring the structure of BERT through Kernel Learning

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

Learning adaptive representations for entity recognition in the biomedical domain

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

Answer Sentence Selection Using Local and Global Context in Transformer Models

Alessandro Moschitti, Ivano Lauriola, Alessandro Moschitti, 2021, ECIR.