Fast hyperparameter selection for graph kernels via subsampling and multiple kernel learning. - Michele Donini; Nicolò Navarin; Ivano Lauriola; Fabio Aiolli; Fabrizio Costa (ESANN, 2017)

Learning dot-product polynomials for multiclass problems. - Ivano Lauriola; Michele Donini; Fabio Aiolli (ESANN, 2017)

Radius-Margin Ratio Optimization for Dot-Product Boolean Kernel Learning. - Ivano Lauriola; Mirko Polato; Fabio Aiolli (ICANN (2), 2017)

Classification of Categorical Data in the Feature Space of Monotone DNFs. - Mirko Polato; Ivano Lauriola; Fabio Aiolli (ICANN (2), 2017)

Learning Deep Representations for Natural Language Processing Applications. - Ivano Lauriola (DC@AI*IA, 2018)

Learning Representations for Biomedical NER. - Ivano Lauriola; Riccardo Sella; Fabio Aiolli; Alberto Lavelli; Fabio Rinaldi 001 (NL4AI@AI*IA, 2018)

The minimum effort maximum output principle applied to Multiple Kernel Learning. - Ivano Lauriola; Mirko Polato; Fabio Aiolli (ESANN, 2018)

Learning Preferences for Large Scale Multi-label Problems. - Ivano Lauriola; Mirko Polato; Alberto Lavelli; Fabio Rinaldi 001; Fabio Aiolli (ICANN (1), 2018)

A Novel Boolean Kernels Family for Categorical Data. - Mirko Polato; Ivano Lauriola; Fabio Aiolli (Entropy, 2018)

Do people believe in Artificial Intelligence?: A cross-topic multicultural study. - Agnieszka Kolasinska; Ivano Lauriola; Giacomo Quadrio (GOODTECHS, 2019)

Evaluation of Tag Clusterings for User Profiling in Movie Recommendation. - Guglielmo Faggioli; Mirko Polato; Ivano Lauriola; Fabio Aiolli (ICANN (Workshop), 2019)

Playing the Large Margin Preference Game. - Mirko Polato; Guglielmo Faggioli; Ivano Lauriola; Fabio Aiolli (ICANN (2), 2019)

Psychiatric Disorders Classification with 3D Convolutional Neural Networks. - Stefano Campese; Ivano Lauriola; Cristina Scarpazza; Giuseppe Sartori; Fabio Aiolli (INNSBDDL, 2019)

A Preference-Learning Framework for Modeling Relational Data. - Ivano Lauriola; Mirko Polato; Guglielmo Faggioli; Fabio Aiolli (INNSBDDL, 2019)

Automatic Detection of Cross-language Verbal Deception. - Pasquale Capuozzo; Ivano Lauriola; Carlo Strapparava; Fabio Aiolli; Giuseppe Sartori (CogSci, 2020)

Exploring the feature space of character-level embeddings. - Ivano Lauriola; Stefano Campese; Alberto Lavelli; Fabio Rinaldi 001; Fabio Aiolli (ESANN, 2020)

Language processing in the era of deep learning. - Ivano Lauriola; Alberto Lavelli; Fabio Aiolli (ESANN, 2020)

Monotone Deep Spectrum Kernels. - Ivano Lauriola; Fabio Aiolli (ICANN (1), 2020)

DecOp: A Multilingual and Multi-domain Corpus For Detecting Deception In Typed Text. - Pasquale Capuozzo; Ivano Lauriola; Carlo Strapparava; Fabio Aiolli; Giuseppe Sartori (LREC, 2020)

Context-based Transformer Models for Answer Sentence Selection. - Ivano Lauriola; Alessandro Moschitti (CoRR, 2020)

MKLpy: a python-based framework for Multiple Kernel Learning. - Ivano Lauriola; Fabio Aiolli (CoRR, 2020)

Enhancing deep neural networks via multiple kernel learning. - Ivano Lauriola; Claudio Gallicchio; Fabio Aiolli (Pattern Recognit., 2020)

Learning deep kernels in the space of monotone conjunctive polynomials. - Ivano Lauriola; Mirko Polato; Fabio Aiolli (Pattern Recognit. Lett., 2020)

Answer Sentence Selection Using Local and Global Context in Transformer Models. - Ivano Lauriola; Alessandro Moschitti (ECIR (1), 2021)

Exploring the structure of BERT through Kernel Learning. - Ivano Lauriola; Alberto Lavelli; Alessandro Moschitti; Fabio Aiolli (IJCNN, 2021)

Learning adaptive representations for entity recognition in the biomedical domain. - Ivano Lauriola; Fabio Aiolli; Alberto Lavelli; Fabio Rinaldi 001 (J. Biomed. Semant., 2021)

FocusQA: Open-Domain Question Answering with a Context in Focus. - Gianni Barlacchi; Ivano Lauriola; Alessandro Moschitti; Marco Del Tredici; Xiaoyu Shen 001; Thuy Vu; Bill Byrne; Adrià de Gispert (EMNLP (Findings), 2022)

Building a Dataset for Automatically Learning to Detect Questions Requiring Clarification. - Ivano Lauriola; Kevin Small; Alessandro Moschitti (LREC, 2022)

An introduction to Deep Learning in Natural Language Processing: Models, techniques, and tools. - Ivano Lauriola; Alberto Lavelli; Fabio Aiolli (Neurocomputing, 2022)

Accurate Training of Web-based Question Answering Systems with Feedback from Ranked Users. - Liang Wang; Ivano Lauriola; Alessandro Moschitti (ACL (industry), 2023)

QUADRo: Dataset and Models for QUestion-Answer Database Retrieval. - Stefano Campese; Ivano Lauriola; Alessandro Moschitti (EMNLP (Findings), 2023)

Pre-Training Methods for Question Reranking. - Stefano Campese; Ivano Lauriola; Alessandro Moschitti (EACL (2), 2024)

Analyzing and Improving Coherence of Large Language Models in Question Answering. - Ivano Lauriola; Stefano Campese; Alessandro Moschitti (NAACL (Long Papers), 2025)

Improving Document Retrieval Coherence for Semantically Equivalent Queries. - Stefano Campese; Alessandro Moschitti; Ivano Lauriola (CoRR, 2025)