227 citations · 435 across the 22 of their papers we have counts for
24 papers
Multitask Kernel-based Learning with Logic Constraints
Michelangelo Diligenti, Marco Gori, Marco Maggini +1
This paper presents a general framework to integrate prior knowledge in the form of logic constraints among a set of task functions into kernel machines. The logic propositions pro…
Neural paraphrasing by automatically crawled and aligned sentence pairs
Achille Globo, Antonio Trevisi, Andrea Zugarini +3
Paraphrasing is the task of re-writing an input text using other words, without altering the meaning of the original content. Conversational systems can exploit automatic paraphras…
Multitask Kernel-based Learning with First-Order Logic Constraints
Michelangelo Diligenti, Marco Gori, Marco Maggini +1
In this paper we propose a general framework to integrate supervised and unsupervised examples with background knowledge expressed by a collection of first-order logic clauses into…
Logic Explained Networks
Gabriele Ciravegna, Pietro Barbiero, Francesco Giannini +4
The large and still increasing popularity of deep learning clashes with a major limit of neural network architectures, that consists in their lack of capability in providing human-…
Generate and Revise: Reinforcement Learning in Neural Poetry
Andrea Zugarini, Luca Pasqualini, Stefano Melacci +1
Writers, poets, singers usually do not create their compositions in just one breath. Text is revisited, adjusted, modified, rephrased, even multiple times, in order to better conve…
Vulgaris: Analysis of a Corpus for Middle-Age Varieties of Italian Language
Andrea Zugarini, Matteo Tiezzi, Marco Maggini
Italian is a Romance language that has its roots in Vulgar Latin. The birth of the modern Italian started in Tuscany around the 14th century, and it is mainly attributed to the wor…
Focus of Attention Improves Information Transfer in Visual Features
Matteo Tiezzi, Stefano Melacci, Alessandro Betti +2
Unsupervised learning from continuous visual streams is a challenging problem that cannot be naturally and efficiently managed in the classic batch-mode setting of computation. The…
Deep Constraint-based Propagation in Graph Neural Networks
Matteo Tiezzi, Giuseppe Marra, Stefano Melacci +1
The popularity of deep learning techniques renewed the interest in neural architectures able to process complex structures that can be represented using graphs, inspired by Graph N…
Relational Neural Machines
Giuseppe Marra, Michelangelo Diligenti, Francesco Giannini +2
Deep learning has been shown to achieve impressive results in several tasks where a large amount of training data is available. However, deep learning solely focuses on the accurac…
Local Propagation in Constraint-based Neural Network
Giuseppe Marra, Matteo Tiezzi, Stefano Melacci +3
In this paper we study a constraint-based representation of neural network architectures. We cast the learning problem in the Lagrangian framework and we investigate a simple optim…
A Lagrangian Approach to Information Propagation in Graph Neural Networks
Matteo Tiezzi, Giuseppe Marra, Stefano Melacci +2
In many real world applications, data are characterized by a complex structure, that can be naturally encoded as a graph. In the last years, the popularity of deep learning techniq…
Conditions for Unnecessary Logical Constraints in Kernel Machines
Francesco Giannini, Marco Maggini
A main property of support vector machines consists in the fact that only a small portion of the training data is significant to determine the maximum margin separating hyperplane…
Neural Poetry: Learning to Generate Poems using Syllables
Andrea Zugarini, Stefano Melacci, Marco Maggini
Motivated by the recent progresses on machine learning-based models that learn artistic styles, in this paper we focus on the problem of poem generation. This is a challenging task…
Video Surveillance of Highway Traffic Events by Deep Learning Architectures
Matteo Tiezzi, Stefano Melacci, Marco Maggini +1
In this paper we describe a video surveillance system able to detect traffic events in videos acquired by fixed videocameras on highways. The events of interest consist in a specif…
Learning in Text Streams: Discovery and Disambiguation of Entity and Relation Instances
Marco Maggini, Giuseppe Marra, Stefano Melacci +1
We consider a scenario where an artificial agent is reading a stream of text composed of a set of narrations, and it is informed about the identity of some of the individuals that…
An Unsupervised Character-Aware Neural Approach to Word and Context Representation Learning
Giuseppe Marra, Andrea Zugarini, Stefano Melacci +1
In the last few years, neural networks have been intensively used to develop meaningful distributed representations of words and contexts around them. When these representations, a…
On the relation between Loss Functions and T-Norms
Francesco Giannini, Giuseppe Marra, Michelangelo Diligenti +2
Deep learning has been shown to achieve impressive results in several domains like computer vision and natural language processing. A key element of this success has been the devel…
T-Norms Driven Loss Functions for Machine Learning
Giuseppe Marra, Francesco Giannini, Michelangelo Diligenti +2
Neural-symbolic approaches have recently gained popularity to inject prior knowledge into a learner without requiring it to induce this knowledge from data. These approaches can po…
COCO_TS Dataset: Pixel-level Annotations Based on Weak Supervision for Scene Text Segmentation
Simone Bonechi, Paolo Andreini, Monica Bianchini +1
The absence of large scale datasets with pixel-level supervisions is a significant obstacle for the training of deep convolutional networks for scene text segmentation. For this re…
On a Convex Logic Fragment for Learning and Reasoning
Francesco Giannini, Michelangelo Diligenti, Marco Gori +1
In this paper we introduce the convex fragment of Łukasiewicz Logic and discuss its possible applications in different learning schemes. Indeed, the provided theoretical results ar…
Aligned and Non-Aligned Double JPEG Detection Using Convolutional Neural Networks
Mauro Barni, Luca Bondi, Nicolò Bonettini +5
Due to the wide diffusion of JPEG coding standard, the image forensic community has devoted significant attention to the development of double JPEG (DJPEG) compression detectors th…
The principle of cognitive action - Preliminary experimental analysis
Marco Gori, Marco Maggini, Alessandro Rossi
In this document we shows a first implementation and some preliminary results of a new theory, facing Machine Learning problems in the frameworks of Classical Mechanics and Variati…
Collapsing of dimensionality
Marco Gori, Marco Maggini, Alessandro Rossi
We analyze a new approach to Machine Learning coming from a modification of classical regularization networks by casting the process in the time dimension, leading to a sort of col…
Learning to see like children: proof of concept
Marco Gori, Marco Lippi, Marco Maggini +1
In the last few years we have seen a growing interest in machine learning approaches to computer vision and, especially, to semantic labeling. Nowadays state of the art systems use…