Search Results for author: Marco Lippi

Found 18 papers, 7 papers with code

The KANDY Benchmark: Incremental Neuro-Symbolic Learning and Reasoning with Kandinsky Patterns

1 code implementation27 Feb 2024 Luca Salvatore Lorello, Marco Lippi, Stefano Melacci

Artificial intelligence is continuously seeking novel challenges and benchmarks to effectively measure performance and to advance the state-of-the-art.

Benchmarking Binary Classification

Band-Pass Filtering with High-Dimensional Time Series

no code implementations11 May 2023 Alessandro Giovannelli, Marco Lippi, Tommaso Proietti

The paper deals with the construction of a synthetic indicator of economic growth, obtained by projecting a quarterly measure of aggregate economic activity, namely gross domestic product (GDP), into the space spanned by a finite number of smooth principal components, representative of the medium-to-long-run component of economic growth of a high-dimensional time series, available at the monthly frequency.

Time Series Vocal Bursts Intensity Prediction

High-dimensional dynamic factor models: a selective survey and lines of future research

no code implementations15 Feb 2022 Marco Lippi, Manfred Deistler, Brian Anderson

High-Dimensional Dynamic Factor Models are presented in detail: The main assumptions and their motivation, main results, illustrations by means of elementary examples.

Individual and Collective Autonomous Development

no code implementations23 Sep 2021 Marco Lippi, Stefano Mariani, Matteo Martinelli, Franco Zambonelli

The increasing complexity and unpredictability of many ICT scenarios let us envision that future systems will have to dynamically learn how to act and adapt to face evolving situations with little or no a priori knowledge, both at the level of individual components and at the collective level.

Tree-Constrained Graph Neural Networks For Argument Mining

1 code implementation2 Sep 2021 Federico Ruggeri, Marco Lippi, Paolo Torroni

By imposing a series of regularization constraints to the learning problem, we exploit a pooling mechanism that incorporates such notion of fragments within the node soft assignment function that produces the embeddings.

Argument Mining Sentence +1

Cross-lingual Annotation Projection in Legal Texts

1 code implementation COLING 2020 Andrea Galassi, Kasper Drazewski, Marco Lippi, Paolo Torroni

We study annotation projection in text classification problems where source documents are published in multiple languages and may not be an exact translation of one another.

Cross-Lingual Transfer Dynamic Time Warping +5

Memory networks for consumer protection:unfairness exposed

no code implementations24 Jul 2020 Federico Ruggeri, Francesca Lagioia, Marco Lippi, Paolo Torroni

Recent work has demonstrated how data-driven AI methods can leverage consumer protection by supporting the automated analysis of legal documents.

Parallelizing Machine Learning as a Service for the End-User

no code implementations28 May 2020 Daniela Loreti, Marco Lippi, Paolo Torroni

As ML applications are becoming ever more pervasive, fully-trained systems are made increasingly available to a wide public, allowing end-users to submit queries with their own data, and to efficiently retrieve results.

BIG-bench Machine Learning

Neural-Symbolic Argumentation Mining: an Argument in Favor of Deep Learning and Reasoning

no code implementations22 May 2019 Andrea Galassi, Kristian Kersting, Marco Lippi, Xiaoting Shao, Paolo Torroni

Deep learning is bringing remarkable contributions to the field of argumentation mining, but the existing approaches still need to fill the gap toward performing advanced reasoning tasks.

Component Classification Link Prediction +3

Attention in Natural Language Processing

no code implementations4 Feb 2019 Andrea Galassi, Marco Lippi, Paolo Torroni

Attention is an increasingly popular mechanism used in a wide range of neural architectures.

Natural Language Statistical Features of LSTM-generated Texts

no code implementations10 Apr 2018 Marco Lippi, Marcelo A Montemurro, Mirko Degli Esposti, Giampaolo Cristadoro

In particular, we characterized the statistical structure of language by assessing word-frequency statistics, long-range correlations, and entropy measures.

Image Captioning Text Generation

Learning to see like children: proof of concept

no code implementations11 Aug 2014 Marco Gori, Marco Lippi, Marco Maggini, Stefano Melacci

In the last few years we have seen a growing interest in machine learning approaches to computer vision and, especially, to semantic labeling.

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